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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)

<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)

Security Engineer, Applied AI

Palo Alto Networks

<div><div>Santa Clara, California, United States of America
 
New York, New York, United States of America
 
Plano, Texas, United States of America Product Engineering Ref ID: JR-020960</div><div> 
</div><div>Our Mission
At Palo Alto Networks&reg;, we&rsquo;re united by a shared mission&mdash;to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you&rsquo;re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you&rsquo;re in the right place.
Who We Are
In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
We believe collaboration thrives in person. That&rsquo;s why most of our teams work from the office full time, with flexibility when it&rsquo;s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.
Job Summary
As a Forward Deployed Engineer (FDE) for AI Gateway, you are a hands-on developer and systems architect who embeds with customer engineering teams. You write production code, design low-latency topologies, and build custom plugins to ship secure enterprise AI workloads to production. You bridge the gap between customer production environments and core engineering&mdash;extending the platform edge while directly contributing code back to the core AI Gateway engine.
Key Responsibilities
<ul><li>Write production-grade code (Python, Go, TypeScript) to integrate AI Gateway with microservices, API meshes, and multi-cloud architectures.
</li><li>Build custom middleware/plugins for identity-aware policies, prompt security, dynamic routing, and telemetry pipelines.
</li><li>Develop automated deployment modules (Terraform, Helm, Kubernetes) and SDK wrappers.
</li><li>Optimize high-throughput, low-latency traffic paths (streaming payloads, caching, load balancing).
</li><li>Lead Architectural Design Reviews (ADRs) with customer Principal Engineers and CISOs for zero-trust deployments.
</li></ul>Qualifications
Required Qualifications
<ul><li>7+ years writing production code (Python, Go, TypeScript/C++), with deep experience in APIs (gRPC, REST, WebSockets) and API gateways (Envoy, Kong).
</li><li>Hands-on experience with LLM orchestration, prompt security, token optimization, model routing, and vector databases/RAG architectures.
</li><li>Proficiency in Kubernetes, Docker, Terraform, AWS/GCP/Azure, OIDC/OAuth2, and zero-trust networking.
</li></ul>Preferred Qualifications
<ul><li>A hands-on builder who loves pair-programming with customer devs and digging into raw code/traces to solve live outages.
</li><li>Experience thinking like an engineer first and a consultant second.
</li><li>Proven ability to own problems end-to-end.
</li><li>Ability to whiteboard enterprise architecture, debug an API integration, review code, and influence the product roadmap.
</li></ul>Compensation Disclosure
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
$147,000.00 - $237,500.00/yr
Our Commitment
We&rsquo;re trailblazers that dream big, take risks, and challenge cybersecurity&rsquo;s status quo. It&rsquo;s simple: we can&rsquo;t accomplish our mission without diverse teams innovating, together.
We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com.
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship?: Yes</div></div>

Senior Forward Deployed Engineer (Customer Engineering)

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

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