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principal full stack software engineer

Butterfly Network

<div><h2 class="jobSectionHeader">Principal Full Stack Engineer</h2>
<h2 class="jobSectionHeader">Company Description</h2>

Butterfly Network, Inc. (NYSE: BFLY) is driving a digital revolution in ultrasound imaging and sensing with its proprietary Ultrasound-on-Chip&trade; semiconductor technology and software solutions. Butterfly first proved its technology in the point-of-care ultrasound market &ndash; commercializing the world's first single-probe, whole-body portable ultrasound device, which is now on its best-selling, third-generation: Butterfly iQ3&trade;. The Company combines its advanced hardware with cloud software and AI, an enterprise workflow solution (Compass AI&trade;) and other offerings to drive adoption of affordable, accessible ultrasound. Butterfly also enables third-party development of imaging AI apps through Butterfly Garden&trade;, its software development kit and AI partnership initiative.

In addition to its medical imaging products, Butterfly Embedded&trade; is the Company's Ultrasound-on-Chip&trade; licensing and co-development program designed to enable a new wave of ultrasound-enabled technologies across non-competitive healthcare markets and beyond. Through Butterfly Embedded&trade;, partners can build and scale novel ultrasound applications powered by Butterfly's proprietary semiconductor chip and software platform. Butterfly's innovations have been recognized by Prix Galien USA, Fierce 50, TIME's Best Inventions and Fast Company's World Changing Ideas, among other achievements.

We're a team of bold thinkers, problem-solvers, and innovators ready to shape the future of medical imaging. Let's build something extraordinary together! 

<h2 class="jobSectionHeader">
Job Description</h2>

We are seeking an experienced software engineer to build our critical Enterprise Clinical workflows system. The Butterfly Cloud provides a secure and robust connection to users' health information. We build tools and services that allow doctors and clinicians to make informed, intelligent diagnostic decisions with the help of their fellow peers. In doing so, we manage and maintain our customers' administration of users and organizations, ensuring feature and entitlement management, as well as building scalable, platform-level enterprise features such as global search and audit logging. Join us in solving challenging, mission-critical problems that will make our technology accessible to 40 million physicians and billions of people worldwide.

As part of our team, your core responsibilities will be to:
<ul>
<li>Solve distributed systems problems, designing for elasticity, reliability, performance, and automated validation</li>
<li>Build modern solutions using the best technologies available, informed by a deep understanding of cloud architecture and how distributed systems operate at scale</li>
<li>Own business problems, shape ideas into system designs, and lead developers through execution</li>
<li>Mentor and lead other engineers to achieve our goals</li>
<li>Perform a wide variety of tasks in support of the role and responsibilities.</li></ul> 

<h2 class="jobSectionHeader">
Qualifications</h2>

Baseline skills/experiences/attributes:
<ul>
<li>10+ years of experience solving distributed systems/web development problems</li>
<li>A track record of mentoring engineers</li>
<li>Willingness to work in different layers of the stack and unfamiliar problem domains</li>
<li>Bachelor's Degree in Computer Science or equivalent experience</li>
</ul>
Ideally, you also have skills and experience in these areas (but it's ok if you don't!):
<ul>
<li>GraphQL and related frameworks e.g. Relay, Apollo and URQL</li>
<li>Experience with LLMs and MLOps</li>
<li>Containerization and orchestration technologies such as Docker, ECS, EKS</li>
<li>Web apps with live updates - pub/sub solutions (such as Redis), WebSockets</li>
<li>Designing and building observability solutions, utilizing modern monitoring, logging, and metrics tools to ensure overall system health</li>
<li>Frontend experience with React and TypeScript</li>
<li>OpenSearch or other Lucene-based search engines</li>
<li>HIPAA, PHI, and PII compliance</li></ul> 

<h2 class="jobSectionHeader">
Values</h2>

Innovation is what we do. Our values are how we make it happen. Butterflies are and believe in&hellip;
<ul>
<li>Patient-Centric Innovators: Our mission is THE mission.</li>
<li>Empowered to Impact: Every voice matters.</li>
<li>One Team, One Goal: Unity fuels progress.</li>
<li>Growth Champions: We embrace challenges.</li>
<li>Action-Oriented Achievers: We follow through, every time.</li></ul> 

<h2 class="jobSectionHeader">
Location</h2>

Butterfly offers a hybrid work model for most positions, with team members spending two or more days a week in the office. While flexibility is key, we value in-person connections that spark creativity and teamwork. Our offices are designed for collaboration, with comfortable workspaces, stocked kitchens, and opportunities to connect with peers.

This role is based in our New York City office, where we strongly value in-person collaboration. For exceptional candidates, we are also open to remote arrangements within the United States, with periodic travel to New York City for team collaboration and planning.<h2 class="jobSectionHeader"> 
Benefits and Perks</h2>
<ul><li>Comprehensive health insurance, encompassing dental and vision coverage, is provided to all our employees. As a health-tech company, we prioritize the well-being of our teams. Additionally, employees have the option to buy up for enhanced health insurance coverage. We also contribute to Health Savings Account (HSA) accounts for all enrolled employees on an annual basis.</li>
<li>Comprehensive Employee Assistance Program - we provide access to tools and resources to support your emotional health and day-to-day needs.</li>
<li>401k plan and match - we facilitate your retirement goals.</li>
<li>Eligible employees will have the opportunity to participate in the Employee Stock Purchase Plan (ESPP)</li>
<li>Unlimited Paid Time Off + 10 Holiday Days a Year - recharge and come back ready to make an impact</li>
<li>Parental Leave - we aim to provide our employees with time to bond with their growing family, along with additional support for primary caregivers to help transition back to work</li>
<li>Competitive salaried compensation - we value our employees and show it</li>
<li>Equity - we want every employee to be a stakeholder</li>
<li>The opportunity to build a revolutionary healthcare product and save millions of lives!</li></ul> 

<h3 class="jobSectionHeader">
Compensation</h3>

Our estimated salary for this role is between $200,000 - $230,000 + bonus + equity + benefits. Actual pay is determined by multiple factors such as location (and hybrid / remote setup), skills, qualifications, experience and market demand. 
Candidates must be authorized to work in the United States. Butterfly Network will not provide immigration sponsorship of any kind for this position, including but not limited to H-1B, TN, O-1, L-1, or green card sponsorship (this includes applicants that are in the process of obtaining a Green Card), now or in the future.

Butterfly Network does not accept agency resumes.

Butterfly Network is an E-Verify Company.

Butterfly Network is an equal opportunity employer. Regardless of race, traits associated with race, color, ancestry, religion, gender, national origin, sexual orientation, age, citizenship, marital status, disability or Veteran status. All your information will be kept confidential according to EEO guidelines.

Butterfly requires security adherence responsibilities from all employees. These include: adhering to all company security policies and procedures, utilize provided company assets securely, and complete all required security awareness training programs. Safeguarding company data and systems from unauthorized access, modification, or destruction, contributing to the overall security posture of the organization. Immediately reporting any suspected or actual security incidents, including phishing attempts, malware infections, or unauthorized access, following the established incident response procedures. 


#LI-KG

#KG-LI</div>

Principal Full Stack Software Engineer

New York Life

<div><div><div><div><h2 class="jobSectionHeader">Job Description</h2>
</div></div><div><div><div><h4 class="jobSectionHeader">Requisition ID</h4>
<div>94763</div>
</div><div><h4 class="jobSectionHeader">Department</h4>
<div>Tech Data AI Ventures</div>
</div><div><h4 class="jobSectionHeader">Job Function</h4>
<div>Tech Data AI Ventures</div>
</div><div><h4 class="jobSectionHeader">Location</h4>
<div>New York,New York,United States</div>
</div><div><h4 class="jobSectionHeader">Role Location Designation</h4>
<div>Hybrid - 3 days per week</div>
</div></div></div><div><div><div><div>Location Designation: Hybrid - 3 days per week
Technology, Data, AI and Ventures:
Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life's businesses. We build solutions that power how we serve policy owners, agents, advisors and employees while delivering measurable business outcomes.
Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader, access to leading-edge technologies and the opportunity to help shape how a world-class financial services company competes in the AI era - all backed by the stability and purpose of a mutual company built to last.
Role Overview
As a Principal AI Engineer within the Artificial Intelligence &amp; Data (AI&amp;D) organization, you will serve as a senior technical leader responsible for designing, building, and delivering enterprise AI solutions that create measurable business value. This is a hands-on engineering role that spans traditional machine learning, Generative AI, and Agentic AI, requiring deep technical expertise across the full AI solution lifecycle&mdash;from opportunity assessment and solution architecture through deployment, monitoring, and continuous improvement.
Working closely with business stakeholders, product managers, data scientists, software engineers, and technology partners, you will lead the delivery of production-ready AI solutions on New York Life's enterprise AI platform. Rather than developing the underlying platform infrastructure, you will leverage enterprise capabilities to rapidly deliver
scalable, secure, and responsible AI applications that solve complex business problems.
In addition to leading technical delivery, you will help define AI engineering standards, influence enterprise AI strategy, mentor engineers, and partner with the business to measure and maximize the value generated by AI investments.
What You'll Do
<ul><li>Lead the end-to-end delivery of AI and Generative AI solutions, partnering with business, product, technology, and data teams to identify opportunities, shape solution strategies, and deliver measurable business outcomes.</li></ul>
<ul><li>Design, develop, deploy, and operate production AI applications using the enterprise AI platform, leveraging existing CI/CD pipelines, infrastructure templates, security controls, and platform services.</li></ul>
<ul><li>Architect and implement advanced AI solutions, including agentic AI systems, multi-agent orchestration, retrieval-augmented generation (RAG), hybrid retrieval strategies, and human-in-the-loop workflows to address complex business challenges.</li></ul>
<ul><li>Evaluate, select, and integrate AI technologies across the solution stack, including foundation models, orchestration frameworks, cloud AI services, and modern software engineering tools, ensuring solutions are scalable, secure, and maintainable.</li></ul>
<ul><li>Establish engineering best practices for AI development, including evaluation frameworks, automated testing, observability, responsible AI, safety validation, and production monitoring.</li></ul>
<ul><li>Rapidly prototype AI-enabled applications and user experiences to validate concepts, accelerate adoption, and inform product direction using modern development frameworks.</li></ul>
<ul><li>Leverage AI-assisted software development tools to accelerate engineering productivity while maintaining high standards for code quality, testing, and governance. Develop internal engineering agents that improve software delivery through automation of testing, code review, deployment validation, and other engineering workflows.</li></ul>
<ul><li>Provide technical leadership, mentorship, and architectural guidance to AI engineers and data scientists, fostering a culture of innovation, experimentation, technical excellence, and continuous learning.</li></ul>
<ul><li>Partner with business leaders to define success metrics, measure solution performance, and continuously optimize AI solutions to maximize business value.</li></ul>
<ul><li>Stay current on emerging AI technologies, evaluate their applicability to enterprise use cases, and influence the organization's AI roadmap and engineering practices.</li></ul>
This role involves limited travel (less than 10%) for vendor meetings, industry conferences, and team collaboration.
What You'll Bring
Required Skills
<ul><li>Master's or PhD in Computer Science, Artificial Intelligence, Engineering, Mathematics, or a related quantitative discipline.</li></ul>
<ul><li>Eight or more years of experience delivering machine learning and AI solutions that solve complex business problems, with increasing technical leadership and ownership.</li></ul>
<ul><li>Demonstrated expertise designing and delivering production AI applications spanning machine learning, Generative AI, and agentic AI architectures.</li></ul>
<ul><li>Strong software engineering skills in Python, with working knowledge of SQL and JavaScript or TypeScript. Experience building, testing, deploying, and supporting production software using modern engineering practices, including CI/CD, code review, Docker, and Kubernetes.</li></ul>
<ul><li>Deep hands-on experience with large language models, prompt engineering, retrieval-augmented generation (RAG), hybrid retrieval techniques, knowledge graphs, and production retrieval architectures.</li></ul>
<ul><li>Experience designing and implementing multi-agent AI systems using modern orchestration frameworks (such as LangGraph, Google ADK, CrewAI, or similar) and tool integration protocols such as MCP or equivalent approaches.</li></ul>
<ul><li>Experience evaluating AI systems using automated evaluation pipelines, safety testing, red teaming, hallucination detection, performance monitoring, and responsible AI practices.</li></ul>
<ul><li>Experience deploying AI solutions on enterprise cloud platforms, particularly Google Cloud Vertex AI, with familiarity across AWS AI services such as Bedrock and SageMaker, as well as modern data platforms including Databricks.</li></ul>
<ul><li>Experience using AI-assisted software engineering tools (such as Codex, Claude Code, or similar) to improve developer productivity, including developing engineering agents that automate software delivery workflows.</li></ul>
<ul><li>Excellent communication, stakeholder management, and collaboration skills with the ability to influence technical direction and communicate effectively with both technical and business audiences.</li></ul>
<ul><li>Demonstrated ability to mentor engineers, lead technical initiatives, and drive engineering excellence across teams.</li></ul>
Preferred Skills
<ul><li>Experience within life insurance, financial services, or other highly regulated industries.</li></ul>
<ul><li>Experience defining enterprise AI architecture, engineering standards, or AI governance frameworks.</li></ul>
<ul><li>Experience leading cross-functional AI transformation initiatives across multiple business domains.</li></ul>
<ul><li>Contributions to the AI community through publications, open-source projects, conference presentations, or technical thought leadership.</li></ul>
Success Looks Like
<ul><li>AI-powered solutions are successfully deployed into production and deliver measurable business value across multiple business domains.</li></ul>
<ul><li>Strong partnerships with business stakeholders result in high adoption, clear business outcomes, and sustained value realization.</li></ul>
<ul><li>Reusable AI solution patterns, engineering practices, and architectural standards accelerate delivery across the organization.</li></ul>
<ul><li>Engineering teams consistently deliver secure, scalable, and responsible AI solutions while embracing AI-assisted development practices.</li></ul>
<ul><li>The organization continues to raise its technical capabilities through your mentorship, innovation, and thought leadership.</li></ul>
Job Level: LEVELPF6
Pay Transparency
Salary Range: $185,000-$264,500
Overtime eligible: Exempt
Discretionary bonus eligible: Yes
Sales bonus eligible: No
Actual base salary will be determined based on several factors but not limited to individual&rsquo;s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.
Company Overview
At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact.
Our diverse business portfolio creates opportunities to make a difference across industries and communities&mdash;inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you&rsquo;ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress.
As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what&rsquo;s next, and your growth powers it.
Our Benefits
We provide a full package of benefits for employees &ndash; and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work. Click here to discover more about our comprehensive benefit options or visit our NYL Benefits Site.
Our Commitment to Inclusion
At New York Life, fostering an inclusive workplace is fundamental to who we are and how we serve our communities. We have a longstanding commitment to creating an environment where individuals can contribute their best and succeed together. This foundation is rooted in our core values of humanity and integrity, ensuring that every employee feels valued and supported. By embracing a broad range of perspectives and experiences, we achieve greater success and fulfill our promise of providing financial security and peace of mind to families across all communities. Click here to learn more about New York Life&rsquo;s leadership in this space.
Recognized as one of Fortune&rsquo;s World&rsquo;s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com. 
Job Requisition ID: 94763
</div>Read More</div></div></div></div></div>

Principal AI Engineer

Capital One

<div>
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 
 Team Description:
 
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 
 In this role, you will:
 
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 
 The Ideal Candidate:
 
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 
 Basic Qualifications:
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications:
 
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </li>
 </ul>
 
 
 Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
 
 
 
 
 The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
 
 
 Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
 
 
 This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
 
 
 Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
 
 
 This role is expected to accept applications for a minimum of 5 business days.
 
 
 No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
 
 
 If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
 
 
 For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
 
 
 Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
 
 
 Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
</div>

Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services)

<div>
 
 Overview
 
 
 
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 Team Description:
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 In this role, you will:
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 The Ideal Candidate:
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 Basic Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </li>
 </ul>
 
 Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
 
 
 
 The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
 
 
 This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
 
 
 Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
 
 
 This role is expected to accept applications for a minimum of 5 business days.
 
 
 No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
 
 
 If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
 
 
 For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
 
 
 Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
 
 
 Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
</div>

Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI)

Qureos

About the company: We build AI hiring agents. They deploy inside the enterprise systems a company already runs, or on the Qureos platform itself for teams who would rather have the whole hiring stack in one place. Either way the agents do the work recruiting teams have always done by hand, from sourcing and screening to interviewing and shortlisting, with speed and consistency no agency or traditional ATS can match. We are a Seed-stage startup backed by Prosus Ventures and COTU Ventures, having raised $5M to accelerate the future of AI-powered hiring. Trusted by more than 1,000 enterprise and public sector organizations, we're scaling rapidly as we build the next generation of AI hiring agents. Operating in a market where every unfilled role and every slow hiring loop costs real money, we are building the future of AI-powered hiring. Our agents let companies run high-volume hiring end to end without ripping out the systems their teams already live in. About the Role As a Forward Deployed Engineer, you will sit at the intersection of engineering, AI, and customer impact. You will work directly with customers to understand how they hire, find the parts of that process worth handing to an agent, and then design, build, and deploy those agents either into the customer's existing enterprise stack or onto the Qureos platform, depending on how they want to run. <ul><li>You will partner closely with customers and Qureos's product and engineering teams to customise agent workflows, improve agent performance, and bring what you learn in live deployments back into the core platform.</li><li>This role is ideal for an engineer who enjoys building production systems, working inside someone else's environment, solving ambiguous problems, and shaping how AI actually gets used in hiring.</li></ul> What You'll Do <ul><li>Embed directly with customers to understand their hiring processes, the systems those processes run on, and where an agent can take over.</li><li>Design, build, and deploy AI hiring agents that source, screen, interview, and move candidates through the funnel.</li><li>Ship those agents into the customer's existing enterprise environment, or onto the Qureos platform for customers who want the all-in-one setup.</li><li>Develop and maintain the infrastructure behind the agents, including APIs, integrations with enterprise ATS and HRIS systems, monitoring, and feedback loops.</li><li>Translate customer requirements into scalable technical solutions and production-ready deployments.</li><li>Collaborate with product and engineering teams to influence roadmap decisions based on what you see in the field.</li><li>Identify patterns across customer deployments and turn one-off integration work into something the platform supports natively.</li><li>Work across engineering, product, and customer teams to ensure successful adoption and long-term impact.</li><li>Operate independently in fast-moving environments where ownership and initiative are highly valued.</li></ul> What You'll Bring <ul><li>3+ years of software engineering experience, preferably with backend, infrastructure, or systems-focused development.</li><li>Strong programming experience in Python (experience with TypeScript/JavaScript is a plus).</li><li>Experience working with cloud platforms such as AWS, GCP, or Azure.</li><li>Ability to design and build reliable production systems, including inside environments you do not control.</li><li>Strong communication skills with the ability to work with both technical and non-technical stakeholders.</li><li>Experience working directly with customers, partners, or cross-functional teams is a plus.</li></ul> Bonus: experience with AI agents, large language models (LLMs), vector databases, prompt engineering, retrieval-augmented generation (RAG), voice agents, or integrating with enterprise ATS and HRIS platforms. Comfortable working in dynamic environments with changing priorities and high ownership. Why Join Us You'll be part of a team building a category-defining AI company in a market that has barely started to change. We move fast, we ship, and we work close to the customer. If you are excited about building AI agents that do real work, deploying them into the systems enterprises actually run, and shaping how hiring gets done, we'd love to hear from you.

Forward Deployed Engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Join the AI Studios Engineering org within Prime Video and Amazon MGM Studios as a Machine Learning Engineer on CreativeFlux, the ML platform powering Nara, our AI-native content creation platform for professional animation and live action/VFX. 
 
You will own the training and serving infrastructure that puts generative models in front of artists working on Prime Video's animated and live action productions. You'll work daily with Applied Scientists, animators, filmmakers, and storytellers, building the systems that turn new model architectures into production-grade tools artists can rely on under tight deadlines. 
 
This role suits engineers who want their work to expand what storytelling can look like, putting new generative capabilities into the hands of the people building Prime Video's animated and live action shows. 
 
Key job responsibilities 
Build and operate ML training and serving infrastructure for the CreativeFlux platform. Strong hands-on experience with EKS / Kubernetes is preferred. 
 
Design, deploy, and operate ML training and inference workloads on EKS, including GPU node groups, custom schedulers, autoscaling, resource quotas, and gang scheduling for multi-GPU jobs 
Integrate generative ML models (image, video, audio) into production inference pipelines, partnering with Applied Scientists to take new architectures from research to scaled deployment 
Build training and fine-tuning pipelines on EKS and SageMaker, including data preparation, distributed training, evaluation harnesses, and checkpointing strategies 
Improve GPU utilization, throughput, and latency on the inference fleet through batching, quantization, model compilation, serving framework tuning, and Kubernetes-native scaling primitives (HPA, KEDA, custom controllers) 
Build automated evaluation pipelines and quality metrics that catch model regressions before they reach Artists, including human-in-the-loop review where needed 
Contribute to integrations with Digital Content Creation (DCC) tools such as Adobe Animate, After Effects, Maya, and Storyboard Pro at the points where models are surfaced to creators 
Own operational health of model endpoints on EKS, including monitoring, alerting, on-call response, capacity planning, and post-incident analysis 
Write clean, well-tested code and participate in design and code reviews 
Stay current with generative ML, distributed training, inference optimization, and GPU efficiency techniques, and apply them where they move team metrics 
 
A day in the life 
As an MLE on the AI Studios team, you'll spend most of your time deploying and tuning generative ML models, optimizing inference pipelines, and building the EKS infrastructure that lets Applied Scientists move new architectures into production. A typical day might include scaling a video generation endpoint to handle a production deadline, debugging a multi-GPU training job that's checkpointing too slowly, or working with a Scientist to take a new image model from a research notebook to a serving fleet. You'll work with other Nara platform teams who owns other building blocks, making sure ML capabilities land cleanly in the workflows artists actually use. You'll participate in team standups, model review sessions, on-call rotations, and platform-wide design reviews with the other Nara teams. You'll learn from experienced engineers and scientists and gradually take on more complex challenges as you grow. 
 
About the team 
We're AI Studios within Prime Video and Amazon MGM Studios, building Nara, our AI-native content creation platform. Our mission is to make Amazon a leader in AI-enabled content creation, giving creators direct control over model outputs while reducing the cost and timeline of animation and live action productions. 
 
Our engineering team spans distributed systems engineers building scalable infrastructure, ML engineers optimizing 1P model training and inference, and full-stack engineers building creative facing agentic tools.
<h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of software development engineer or related occupational experience</li><li>1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience</li><li>1+ years of Object Oriented Design experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Culver City - 143,700.00 - 194,400.00 USD annually 
USA, NY, New York - 158,100.00 - 213,800.00 USD annually</div>

Machine Learning Engineer II , AI Studios

<div>
 
 Overview
 
 
 
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 Team Description:
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 In this role, you will:
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 The Ideal Candidate:
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 Basic Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </li>
 </ul>
 
 Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
 
 
 
 The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
 
 
 This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
 
 
 Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
 
 
 This role is expected to accept applications for a minimum of 5 business days.
 
 
 No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
 
 
 If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
 
 
 For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
 
 
 Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
 
 
 Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
</div>

Lead AI Engineer (FM Hosting, LLM Inference)

Explore 45+ Principal full stack software engineer in New York this September. Find roles across top companies and apply now to boost your career.