Senior Staff AI Engineer

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Collaborate with engineers, research scientists, technical program managers, and product managers to create AI-driven products.

• Design, develop, test, deploy, and maintain AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.

• Utilize open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch.

• Innovate and implement cutting-edge foundation model optimization techniques to enhance scalability, cost, latency, and throughput.

• Contribute to the technical vision and long-term strategic roadmap for foundational AI systems at Capital One.

• Define and guide the technical architecture vision for AI, integrating applied research advancements into dependable, scalable production ecosystems.

• Lead the initiative to establish AI performance, safety, and transparency standards for company-wide model development and deployment.

• Propel multi-year platform projects that unify data, compute, and model lifecycle management within an enterprise AI architecture.

• Mentor senior technical leaders across research, data, and engineering fields.

⛳️ Requirements

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related areas, with at least 10 years of experience in developing AI and ML algorithms or technologies; or a Master’s degree in these fields with at least 8 years of relevant experience.

• A minimum of 10 years of programming experience in Python, Go, Scala, CUDA, or Java.

• Experience in architecting AI platforms while making tradeoff decisions regarding cost, latency, throughput, and accuracy.

• At least 9 years of experience in deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud systems.

• Proven experience in architecting, designing, developing, integrating, delivering, and supporting complex AI systems.

• Demonstrated capability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level.

• Experience in developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang.

• Proficient in developing and applying advanced techniques for optimizing training and inference software.

• Experience in building agentic AI systems and workflows.

• Recognized leadership in the field of applied AI or machine learning infrastructure through patents, publications, or open-source contributions.

• Experience in designing long-term AI infrastructure strategies while balancing cost, scalability, ethics, and regulatory compliance.

• Proven experience in driving organization-wide adoption of AI safety, alignment, and governance standards.

• Ability to influence R&D investment strategy effectively.

• Experience in optimizing models, instance counts, and hardware types.

• Qualified applicants may be eligible for employment authorization sponsorship.

🏝️ Benefits

• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI).

• Comprehensive, competitive, and inclusive health, financial, and other benefits that support total well-being.

• Reasonable accommodations available for applicants who require them.