Build responsible, scalable AI systems that power foundational capabilities across Capital One. This Staff AI Engineer role (remote eligible) focuses on designing and deploying production AI platforms, including model training and inference, agents and multi-agent workflows, evaluation, governance, and observability, while helping shape enterprise AI architecture standards. You will collaborate with engineers and research scientists to deliver AI-powered products that impact how associates work and how customers interact with Capital One.
What you’ll do
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for internal associates and external customers.
- Design, develop, test, deploy, and support AI software components across the lifecycle, including foundation model training, large language model inference, agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Apply a broad stack of AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch (plus additional Open Source and SaaS tools).
- Introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
- Help set the technical vision and long-term roadmap for foundational AI systems at Capital One.
- Set technical direction for enterprise-wide AI architecture by unifying tooling, observability, and deployment standards across teams.
- Own design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads.
- Champion responsible AI principles throughout system design, including transparency, reproducibility, and fairness-by-design.
- Drive internal education and mentorship through architecture councils and AI guilds, sharing best practices across the organization.
Required qualifications
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Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies; or Master’s degree plus at least 6 years.
- At least 8 years programming with Python, Go, Scala, CUDA, or Java.
Helpful experience
- Experience designing AI systems with tradeoffs across cost, latency, throughput, and accuracy.
- 8+ years deploying scalable, 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 the VP level.
- Experience developing AI/ML algorithms 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 optimization techniques to improve hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and agentic workflows.
- 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 to improve resilience, compliance, and compute efficiency.
- Excellent communication skills to articulate complex AI concepts to peers.
- Experience defining north-star metrics that balance business value, innovation velocity, cost, and ethical responsibility.
- Experience right-sizing models, instance counts, and hardware types for requirements such as context length and token inputs/outputs.
Team context
The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life. The team works with partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions that support millions of customers. Their AI models and platforms help teams enhance products with responsible, scalable AI for high-leverage impact.
Technology landscape
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, Java, AWS, Google Cloud, Azure, C++, C#, Golang.
Compensation and location
- Remote (Regardless of Location): $244,700 - $279,200
- McLean, VA: $269,100 - $307,200
Candidates hired in other locations will be offered the pay range associated with that location, as reflected in the offer letter.
Incentives and benefits
- Comprehensive, competitive, and inclusive health, financial, and other benefits to support total well-being.
- Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI), depending on the plan.
Additional details
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- Expected application window: minimum of 5 business days.
- No agencies please.
- Capital One promotes a drug-free workplace and is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws.
If you need accommodation for the recruiting process, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For technical support related to the recruiting process, email Careers@capitalone.com.
