Staff AI Engineer

Capital One is hiring a Staff AI Engineer (remote eligible) to help build and deploy responsible, scalable enterprise AI systems across model training, inference, agents, evaluation, governance, and observability.

Responsibilities

• Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products used by associates and customers
• Design, develop, test, deploy, and support AI components across foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Apply open source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and others
• Introduce optimization techniques for large-scale production AI systems to improve scalability, cost, latency, and throughput
• Shape technical vision and contribute to the long-term roadmap for foundational AI systems at Capital One
• Set technical direction for enterprise-wide AI architecture, unifying tooling, observability, and deployment standards across teams
• Own model routing, caching, and orchestration design and integration for hybrid and multi-model workloads
• Advance responsible AI principles in system design, including transparency, reproducibility, and fairness-by-design
• Support internal enablement through education, mentorship, and best-practice sharing via architecture councils and AI guilds

Requirements

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 8+ years developing AI and ML algorithms or technologies
• OR Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6+ years developing AI and ML algorithms or technologies
• 8+ years programming with Python, Go, Scala, CUDA, or Java

Technologies

• AWS Ultraclusters
• Huggingface
• VectorDBs
• PyTorch
• Python
• Go
• Scala
• CUDA
• Java

Team

• The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life
• Partners with teams across the company to advance science and AI engineering and to build and deploy proprietary solutions
• Builds and deploys AI models and platforms that enable teams to enhance products with responsible, scalable AI at high leverage impact

Benefits

• Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being

Ideal Candidate

• Builds high-quality systems and shares a commitment to doing the right thing
• Stays current with latest research and can understand scientific publications to apply techniques in production
• Thrives in ambiguous, large-scale problems and can explain findings clearly
• Works with strong engineering and mathematics fundamentals and can spot optimization opportunities across hardware, software, and AI
• Demonstrates resilience and can forge new paths when the route is unknown

Preferred Qualifications

• Experience designing AI systems with tradeoffs across cost, latency, throughput, and accuracy
• 8+ years deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
• Ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to VP level
• Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang
• Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost
• Experience building agentic AI systems and agentic workflows
• Excellent communication and presentation skills for articulating complex AI concepts
• Track record defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability, and evaluation frameworks
• Experience leading federated or multi-cloud AI strategies for resilience, compliance, and compute efficiency
• Experience guiding model handoff, evaluation, and productization from research to production
• Experience defining north-star metrics balancing business value, innovation velocity, cost, and ethical responsibility
• Experience right-sizing models, instance counts, and hardware types based on requirements such as context length and token inputs/outputs

Compensation (Remote and Selected Locations)

• Remote (regardless of location): $244,700 - $279,200
• Cambridge, MA: $269,100 - $307,200
• McLean, VA: $269,100 - $307,200
• New York, NY: $293,600 - $335,100
• San Francisco, CA: $293,600 - $335,100
• San Jose, CA: $293,600 - $335,100

Notes

• Capital One is open to hiring a Remote Employee for this opportunity
• Capital One may consider sponsoring a new qualified applicant for employment authorization for this position
• Applications are expected to be accepted 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
• Capital One promotes a drug-free workplace
• For technical support or questions about the recruiting process, email [email protected]