applications engineer

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people worldwide for a better future. 
Job Overview
The Applied AI Engineer (AAE) ensures AI systems work in the real-world contexts they are designed to serve. This works on designing (e.g., building flows and structured agents), deploying, adapting, testing, and validating AI systems in program environments to ensure they are accurate, usable, and effective in practice. 
The AAE works directly with country teams, partners, and communities to configure AI systems for local contexts, including language, cultural nuance, and operational constraints. They are responsible for what goes into the system, how it behaves, and whether it delivers meaningful outcomes for end users, making key implementation decisions on system configuration, behavior and deployment approaches based on field conditions and user needs.
Owning deployments across the full lifecycle, from initial configuration through iteration, evaluation and scale, the AAE translates real-world complexity and field insights into concrete system improvements, product decisions and deployment strategies.
Acting as the bridge between technical development and field implementation, the AAE surfaces failure modes early, strengthens system performance and informs the evolution of tools, workflows and infrastructure required for scalable deployment. The role also identifies patterns across implementations and translates them into reusable frameworks and best practices to improve speed, quality, and consistency across programs. 
 
By enabling high-quality deployments at speed, this role ensures that IRC&rsquo;s investments in AI translate into tangible impact for the people we serve. 
Major Responsibilities
1. AI Deployment, Configuration &amp; Context Adaptation<ul><li>
Lead end-to-end deployment of AI systems in program contexts, from initial scoping and configuration through live use</li><li>
Adapt systems to local environments, including language, cultural context, and operational realities</li><li>
Configure prompts, workflows, and AI System behavior, including conversation flows, instructional logic and user experience Curate, structure, and validate domain-specific knowledge bases including system memory and personalization strategies to improve relevance and continuity</li><li>
Ensure systems reflect real-world humanitarian knowledge that may not exist in training data</li><li>
Support multiple concurrent software deployments</li></ul>
2. Testing, Validation &amp; Continuous Improvement<ul><li>
Test AI systems in real-world conditions to identify failure modes before scale</li><li>
Applies an agile, iterative approach, rapidly building, testing, and refining systems based on real-world feedback, while exercising strong judgment on when to iterate vs. escalate or rethink approach</li><li>
Conduct safety validation and red teaming to identify risks, harms, and unintended consequences ensuring responsible and ethical AI deployment in vulnerable contexts</li><li>
Troubleshoot technical and operational issues, including in low-connectivity environments</li><li>
Collect and interpret user and community feedback on usability, relevance, and performance</li><li>
Escalate systemic issues and collaborate with engineering teams on fixes and improvements</li><li>
Define and track success metrics to evaluate system performance, user engagement and real-world impact over time</li></ul>
3. Partnership &amp; Cross-functional Collaboration<ul><li>
Train field teams on deploying systems and managing structured handovers to ensure adoption and sustained use</li><li>
Document deployment processes, configurations, and lessons learned to build institutional knowledge and support replication</li><li>
Work closely with AI engineers and technical teams to translate field insights into system improvements</li><li>
Collaborate with program teams and partners to align deployments with priorities</li><li>
Act as the primary interface between field teams and technical development during deployment</li><li>
Support scoping and technical input for proposals and cost recovery opportunities where deployment capacity is a factor</li><li>
Ensure solutions are integrated into workflows in ways that are practical, adopted, and sustained</li><li>
Contribute to shared learning across deployments to improve future implementation</li><li>
Identify patterns across deployments and translate them into reusable frameworks and best practices to improve speed and quality for future implementations</li><li>
Contribute to product design and system improvements by translating field insights into system requirements, feature priorities and roadmap input</li></ul> 
Key Working Relationships:<ul><li>
Position Reports to: [Sr. Deployment Engineer]</li><li>
Key Relationships: AI/Technology development teams, IT, Data, regional and country program teams, implementing partners, sector specialists</li></ul> 
Requirements:<ul><li>
3&ndash;5+ years of experience in software engineering, technical implementation, or related roles</li><li>
Proficiency in JavaScript/TypeScript and modern web development practices; comfort with Python or similar scripting languages a plus.</li><li>
Experience deploying and iterating on LLM-based applications in real-world environments</li><li>
Experience with communications or messaging platforms (e.g., Zendesk, WhatsApp, Telegram) preferred</li><li>
Experience integrating AI systems with third-party platforms and business tools (e.g. CRMs, messaging platforms, APIs), with familiarity with common integration patterns, authentication approaches, and data flow considerations.</li><li>
Proficiency with AI-assisted development tools (e.g. Cursor, Claude Code) and a clear-eyed understanding of their limitations and failure modes.</li><li>
Strong problem-solving skills, with the ability to translate real-world challenges into technical solutions</li><li>
Experience working in low-resource, high-complexity, or field-based environments</li><li>
Ability to operate in ambiguous environments and define structure where none exists</li><li>
Strong understanding of how AI systems behave in practice, including limitations and failure modes</li><li>
Ability to work across technical and non-technical teams and translate between them</li><li>
Experience training non-technical users and managing system handovers</li><li>
Experience in humanitarian, development, or nonprofit contexts strongly preferred</li><li>
Familiarity with East or Central Africa contexts preferred</li><li>
Fluency in English required; additional regional language skills preferred</li></ul> 
Working Environment
This position can be based remotely or in an IRC office location. The role requires close collaboration with country teams and may involve travel to field locations. Candidates should be comfortable working across time zones and in dynamic, resource-constrained environments. 
Compensation: (US Pay Rate: 88,277-103,222 USD); (UK Pay Rate: 49,598.90-60,040 GBP) Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements. 
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
Compensation: Posted pay ranges apply to US-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.
US Benefits: We offer a comprehensive and highly competitive set of benefits. In the US, these include: 10 sick days, 10 US holidays, 20-25 paid time off days depending on role and tenure, medical insurance starting at $163 per month, dental starting at $6.50 per month, and vision starting at $5 per month, FSA for healthcare and commuter costs, a 403b retirement savings plans with immediately vested matching, disability &amp; life insurance, and an Employee Assistance Program which is available to our staff and their families to support counseling and care in times of crisis and mental health struggles.
Equal Opportunity Employer: IRC is an Equal Opportunity Employer. IRC considers all applicants on the basis of merit without regard to race, sex, color, national origin, religion, sexual orientation, age, marital status, veteran status, disability or any other characteristic protected by applicable law.
#li-1</div>

Applied AI Enginner

Mercor

<div>
 
 About Mercor
 
 
 
 Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
 
 
 Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You&rsquo;ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
 
 
 
 About The Role
 
 
 
 As a
 
 Software Engineer on Applied AI
 
 , you&rsquo;ll build, deploy, and operate systems that sit directly between frontier AI research and data delivery.
 
 
 This is a high-ownership, deeply technical role. You&rsquo;ll work through ill-defined problems, prototype quickly with researchers and customers, and take systems from early experiments to reliable, scalable production. You&rsquo;ll own projects end-to-end: spanning requirements gathering, creating data creation pipelines, and improving model-adjacent infrastructure, while partnering closely with frontier AI labs and Mercor&rsquo;s internal teams to ship high-impact applied AI solutions.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Partner closely with frontier AI labs to understand their data, post-training, and evaluation needs
 </li>
 <li>
 Build and operate scalable data pipelines for post-training workflows and model evaluations
 </li>
 <li>
 Design and build scalable systems for synthetic data generation and data quality, and work directly with customers to understand requirements and develop technical solutions
 </li>
 <li>
 Prototype new data types, benchmarks, and evaluation frameworks
 </li>
 <li>
 Lead technical discussions with customers
 
 
 </li>
 </ul>
 
 What Makes This Role Different
 
 
 
 <ul>
 <li>
 Direct frontier exposure. You&rsquo;ll work closely with researchers at leading AI labs, building infrastructure that directly accelerates cutting-edge research.
 </li>
 <li>
 Coding + customer work. This role blends deep technical execution with customer interaction. Engineers who enjoy both building and communicating tend to thrive.
 
 
 </li>
 </ul>
 
 Day-to-Day
 
 
 
 <ul>
 <li>
 Fast-moving, high-ownership environment
 </li>
 <li>
 Technically demanding, collaborative work
 </li>
 <li>
 &ldquo;Building the plane while flying it&rdquo;
 </li>
 <li>
 In-person culture (SF, 181 Fremont)
 </li>
 <li>
 Aligned with frontier research timelines
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Strong backend engineering fundamentals in a modern language (Python, Go, Rust, etc.)
 </li>
 <li>
 Experience with model training and inference
 </li>
 <li>
 Strong grounding in statistical analysis and experimental design for measuring model performance and improvements
 </li>
 <li>
 Familiarity with evaluation methods for large language models
 </li>
 <li>
 Comfort working through ambiguity and shipping iteratively
 
 
 </li>
 </ul>
 
 You&rsquo;re Likely Someone Who
 
 
 
 <ul>
 <li>
 Enjoys ownership and customer-facing problem solving
 </li>
 <li>
 Thinks entrepreneurially and moves quickly
 </li>
 <li>
 Balances speed with engineering rigor
 </li>
 <li>
 Communicates clearly with technical and non-technical users
 
 
 </li>
 </ul>
 
 Why Engineers Join
 
 
 
 <ul>
 <li>
 Direct exposure to frontier AI research
 </li>
 <li>
 Real ownership and visible impact
 </li>
 <li>
 Technical depth paired with human interaction
 </li>
 <li>
 Fast feedback loops and high leverage
 </li>
 <li>
 There are very few roles that combine this level of technical rigor, customer proximity, and research exposure.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Bi-annual performance bonus structure
 </li>
 <li>
 Generous equity grant vested over 4 years
 </li>
 <li>
 Up to $15k Relocation bonus
 </li>
 <li>
 $10K proximity bonus (if you live within 0.5 miles of our office)
 </li>
 <li>
 $1.5K monthly stipend for meals
 </li>
 <li>
 Free Equinox membership
 </li>
 <li>
 $200 monthly laundry reimbursement
 </li>
 <li>
 $200 monthly personal wellness reimbursement
 </li>
 <li>
 Health, Dental, Vision insurance
 
 
 </li>
 </ul>
 Compensation Range: $130K - $500K
 
 
</div>

Software Engineer, Applied AI

Eagle

<div>About Eagle
We&rsquo;re on a mission to radically transform the way we design and construct our built environment.
Backed by Lightspeed Venture Partners, Eagle acquires and transforms civil, structural, and MEP engineering firms with applied AI. We&rsquo;re an AI laboratory dedicated to providing engineers with the tools they need to solve the world&rsquo;s hardest infrastructure, energy, and climate problems.
By arming designers with frontier technology, our ambition is to build the most valuable, talent-dense engineering firm in the United States.
The opportunity
Our core thesis: 85% of what engineers do today is theoretically automatable, yet less than 5% has actually been touched by AI. That gap is the largest of any profession. Our plan is to close it by acquiring engineering firms, building purpose-built tools for their staff, and compounding that proprietary intelligence across acquisitions.
As an Applied AI Engineer, you'll work directly with the founders and staff at engineering firms to ship the initial iterations of our operating system that will power this transformation. You'll own outcomes at the edge and get a front-row seat to building a company from zero&mdash;engaging with architecture decisions, firm acquisitions, and product strategy&mdash;on a problem domain that's barely been touched by AI.
What you'll do<ul><li>
Embed with staff at engineering firms alongside the founders; then come back and build against what you saw</li><li>
Own problems end-to-end from problem discovery to deployment to debugging in prod</li><li>
Collaborate directly with the CTO on engineering culture, technical direction, and what we&rsquo;ll build next</li></ul>
What we look for<ul><li>
Has a deep curiosity for how things work (e.g., an organization, a workflow, a market)</li><li>
Isn&rsquo;t afraid to expose their ignorance and is constantly asking why</li><li>
Has the poise and communication skills to earn trust with people who've never worked with a tech company before</li><li>
Can sit with noisy, conflicting feedback from users and distill it into a clear opinion about what to build</li><li>
Is willing to get on a plane with us</li><li>
Has experience or interest in LLMs, Agent Frameworks, RAG, browser automation, or doc parsing</li><li>
Is not above any task: Up to write the web scraper, help users leverage off-the-shelf tools, or build the plugin for Windows native AEC software</li></ul>
Compensation<ul><li>
Competitive cash compensation ($150K&ndash;$300K depending on experience)</li><li>
Meaningful early-stage equity</li><li>
Full healthcare benefits</li><li>
In-person office in NYC with team meals</li></ul></div>

Applied AI Engineer

Millennium Management

<div>Full Stack Engineer - Portfolio Team
Our hedge fund is looking for a talented engineer to work across the stack to build a platform for one of Millennium's portfolio management teams. Projects will have a substantial impact on trading and analytics tooling with the expectation to expand ambition and scope over time.
The successful candidate will combine strong technical skills, a passion for creative problem solving, and an intense curiosity. The group is looking for a versatile strong Python coder whose main responsibility will be to develop the platform for the portfolio management team within the firm. This is an ideal opportunity for a strong engineer that is looking to work within a trading team.
Principal Responsibilities<ul><li>
Rapid development and release of applications: process automation, intelligent alerts, interactive visualizations, and portfolio analysis tooling</li><li>
Develop and enhance the existing platform for quantitative and portfolio manager team members</li><li>
Work on building out the Python codebase using the FastAPI, Flask, or other web frameworks</li><li>
Oversee the entire full stack development of the platform</li><li>
Integrate market data APIs from vendors and Millennium&rsquo;s own database and transform the data for the team&rsquo;s non-relational database</li><li>
Collaborate with team on best practices and overall business strategy</li></ul>
Qualifications/Skills Required<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline</li><li>
4+ years of professional software or quant engineering experience</li><li>
Strong applied knowledge of web base application development using React and/or Angular</li><li>
Strong programming skills in Python both in web application development and data engineering/science tooling such as Numpy, Pandas, and/or PyTorch</li><li>
Experience AI forward deployments agent orchestration frameworks &amp; MCP</li><li>
Strong SQL experience preferred for the pricing model's performance</li><li>
Experience using agentic coding workflows using Cursor, Claude code, etc.</li><li>
Experience with developing dashboards and other data visualization applications with Plotly, Matplotlib, Bokeh, Dash, etc.</li><li>
Experience using AWS technologies such as S3, Athena, SQS, Batch, Lambda</li><li>
Experience with Linux is a plus</li><li>
Extremely organized and a self-starter with effective multitasking and prioritization skills</li><li>
Highly motivated, willing to take ownership of work, drive to solve problems and work effective under pressure</li><li>
Excellent written and verbal communication skills, willing to proactively engage other team members in fostering a strong collaborative team-oriented environment</li><li>
Good team player with a strong willingness to participate and help others.</li><li>
Able to prioritize in a fast moving, high pressure, constantly changing environment; High sense of urgency</li></ul><div><div><div><div><div><div>
Millennium offers a total compensation package which includes a base salary, discretionary performance bonus, and comprehensive benefits. The estimated base salary range for this position is $150,000 to $200,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual&rsquo;s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.</div></div></div></div></div></div></div>

Full Stack Engineer - Portfolio Team

ALICE + OLIVIA

<div>
 
 Location: New York, NY or Secaucus, NJ (Hybrid)
 
 
 Decision Science Engineer (Applied Data Scientist)
 
 
 
 
 
 
 POSITION SUMMARY:
 
 
 
 ALICE + OLIVIA is hiring a Decision Science Engineer to build, operationalize, and own predictive models that improve decision making across Planning, Merchandising/Buying, Customer 360, and Inventory Management. Working primarily within Palantir Foundry as the core analytics and deployment platform, this role bridges data science and platform engineering, translating real-world commercial constraints including seasonality, product lifecycle, allocations, replenishment, promotions/markdowns, and customer behavior into practical, production-grade, human-in-the-loop models.
 
 
 
 
 
 This is a highly cross-functional role with direct, ongoing exposure to business stakeholders and end users, from planners and buyers who consume and act on model outputs, to the teams working within Foundry Workshop applications day-to-day. Understanding how outputs are used in real workflows, and staying close to the people using them, is central to how this role operates. Sitting within the IT organization and serving the full business including DTC, wholesale, planning, and supply chain, this position carries direct visibility to executive business stakeholders. This role is focused on applied data science, decision-support modeling, and model operationalization, not reporting or core data engineering, while partnering closely with Engineering, BI, and the broader Enterprise Applications team.
 
 
 
 
 
 
 RESPONSIBILITIES:
 
 
 <ul>
 <li>
 Design, build, and maintain predictive and statistical models supporting retail planning, buying, inventory, and demand forecasting.
 </li>
 <li>
 Operationalize models within Palantir Foundry using Code Workbook and Code Repository, working against Snowflake as the primary data source and ensuring outputs are production-grade and maintainable.
 </li>
 <li>
 Own and evolve analytics logic and assumptions embedded in planning and buying workflows.
 </li>
 <li>
 Partner with Planning, Buying, Merchandising, and DTC teams to translate business needs into model-driven insights, maintaining direct, ongoing relationships with the stakeholders and end users consuming model outputs.
 </li>
 <li>
 Collaborate with the Enterprise Applications team on Workshop app development to ensure model outputs are surfaced effectively in business-facing Foundry applications.
 </li>
 <li>
 Build models for customer segmentation, CLV, retention/churn, propensity, and campaign targeting (Customer 360).
 </li>
 <li>
 Collaborate with Engineering, who owns data pipelines and Snowflake ingestion, to ensure model inputs are reliable, well-governed, and fit for purpose without owning the underlying data infrastructure.
 </li>
 <li>
 Support human-in-the-loop workflows where planners and buyers can interrogate, override, or adjust model outputs in real time.
 </li>
 <li>
 Validate model outputs against business reality and historical performance, closing the loop directly with end users on model accuracy and relevance.
 </li>
 <li>
 Document methodologies and assumptions to support long-term ownership and institutional knowledge.
 </li>
 </ul>
 
 
 
 
 
 QUALIFICATIONS:
 
 
 <ul>
 <li>
 4 to 8+ years of experience in data science, applied analytics, or predictive modeling.
 </li>
 <li>
 Strong experience building predictive or statistical models including forecasting, optimization, regression, and classification.
 </li>
 <li>
 Proficiency in Python for data analysis, modeling, and production-grade code.
 </li>
 <li>
 Strong SQL and hands-on experience with Snowflake or equivalent cloud data warehouse.
 </li>
 <li>
 Experience with Palantir Foundry strongly preferred, including familiarity with the Foundry Ontology layer, analytics and modeling tooling (Code Workbook, Code Repository), and how model outputs are surfaced through business-facing applications. Candidates who can reason within and contribute to an existing Ontology, and who understand how the semantic data layer connects to model design, will be prioritized.
 </li>
 <li>
 Familiarity with experiment design and causal inference.
 </li>
 <li>
 Experience with time-series forecasting at scale.
 </li>
 <li>
 Retail domain experience strongly preferred, including familiarity with demand vs net sales, sell-through, markdowns, planning vs buying workflows, seasons, price groups, and store vs e-commerce dynamics.
 </li>
 <li>
 Experience working with messy, real-world data and designing models that support business judgment.
 </li>
 <li>
 Ability to reason about semantic or ontology-based data models.
 </li>
 <li>
 Strong communication and relationship skills, comfortable working directly with planners, buyers, and business stakeholders, and able to translate model outputs into decisions, not just insights.
 </li>
 <li>
 Long-term ownership mindset for maintaining and evolving models over time.
 </li>
 <li>
 Hands-on experience building or contributing to Palantir Foundry Workshop applications.
 </li>
 <li>
 Background in wholesale or multi-channel retail, including familiarity with the operational differences between DTC, wholesale, and brick-and-mortar planning cycles.
 </li>
 <li>
 Exposure to agent-based or AI-assisted analytics workflows.
 </li>
 <li>
 Experience working within a formal data governance or steerco-driven prioritization structure.
 </li>
 <li>
 Familiarity with Snowflake-native development patterns including dbt, Snowpark, or similar.
 </li>
 </ul>
 
 
 
 
 
 ADDITIONAL INFORMATION:
 
 
 
 This role sits within the IT organization, reporting to the VP of Information Technology, and operates across the full business including Planning, Merchandising/Buying, DTC, and Supply Chain. Engineering owns ETL, data pipelines, and Snowflake ingestion. BI owns reporting and dashboards. This role owns predictive modeling, decision-support analytics, and model operationalization within Palantir Foundry. Work is prioritized through a cross-functional steering committee with direct business stakeholder representation, ensuring this role has structured visibility into commercial priorities and executive-level exposure from day one.
 
 
 
 
 
 ALICE + OLIVIA is at an inflection point in how it uses data to make decisions. This role is central to that transformation, building the analytics capability that connects our Palantir Foundry investment to real commercial outcomes across every part of the business. This is not a role that maintains existing infrastructure or produces reports. It is a greenfield opportunity to own a strategic function, work directly with the teams making decisions, and build something that compounds in value over time. For the right person, it is a rare combination of technical depth, business proximity, and organizational support.
 
 
 
 
 
 $150,000 -175,000 base salary (This range represents the low and high end of the anticipated base salary range for this NY OR NJ - based position. The base salary will depend on numerous factors such as: experience and qualifications for the role, experience level, skillset, and balancing internal equity relative to other A+O employees.)
 
</div>

Data Scientist

Lead, Product Content Engineering

Capital One

<div>Senior Lead Software Engineer, Full Stack (React, Scala)
Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs. We are seeking Full Stack Software Engineers who are passionate about marrying data with emerging technologies. As a Capital One Senior Lead Software Engineer, you&rsquo;ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
About the Team: The Travel Portal Messaging Team is building a ground-up messaging and push notification platform to support Capital One Travel products that will directly connect to users regarding their travel plans. The travel organization primarily develops in the Scala/Finagle stack, and is looking for strong Scala or Functional Java experience, as well as strong communication skills to communicate with the numerous stakeholder teams.
What You&rsquo;ll Do:<ul><li>
Work across Capital One Travel, as we look to develop the platform to support increased personalization, support new and emerging groups of users, and lead a team of developers and designers.</li><li>
Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company</li><li>
Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal &amp; external technology communities, mentoring other members of the engineering community, and from time to time, be asked to code or evaluate code</li><li>
Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment</li><li>
Utilize programming languages like Scala, Java, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 6 years of experience in software engineering (Internship experience does not apply)</li><li>
At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)</li></ul>
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree</li><li>
9+ years of experience in at least one of the following: Scala, Java, Python, or Go</li><li>
4+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service</li><li>
4+ years of experience in open source frameworks</li><li>
1+ years of people management experience</li><li>
2+ years of experience in Agile practices</li><li>
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion</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: $229,900 - $262,400 for Sr. Lead Software Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Software 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>

Senior Lead Software Engineer, Full Stack (React, Scala)

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