AI Engineer 5 (GenAI Platform, Agentic Infrastructure)
$230k - $262k • San Jose, CA • Full-time
Posted 1mo ago
About the job
Capital One is building responsible and reliable AI systems to transform banking. Leveraging extensive experience in machine learning and investments in technology infrastructure, the company aims to lead in enterprise AI adoption. This role is part of the Intelligent Foundations and Experiences (IFX) team, which develops and deploys proprietary AI solutions that are central to the business and impact millions of customers. The team empowers other departments across Capital One to enhance their products with AI in responsible and scalable ways, driving high-leverage impact.
Responsibilities
- Partner with cross-functional teams to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, and observability.
- Leverage Open Source and SaaS AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems.
- Contribute to the technical vision and roadmap of foundational AI systems.
- Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
- Establish and lead cost-performance governance reviews for AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
- Lead team design councils or review boards to ensure technical consistency and compliance with AI engineering standards.
- Mentor AI engineers, fostering cross-domain learning and elevating organizational technical maturity.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, OR Master's degree plus at least 4 years of experience.
- At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
- Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
- 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience designing, developing, delivering, and supporting complex AI systems.
- Experience developing AI and ML algorithms or technologies (e.g., LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Experience in building agentic AI systems and agentic workflows.
- Passion for staying abreast of the latest AI research and judiciously applying novel techniques in production.
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
- Experience architecting and integrating heterogeneous AI systems (rule-based, retrieval-augmented, generative) into unified production pipelines.
- Experience defining and enforcing standards for ethical AI deployment, including explainability and fairness.