Distinguished AI Engineer (Agentic AI Platform)

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world‑class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high‑performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand‑in‑hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Why this Role Matters We are building an enterprise Generative AI Platform that lets dozens of product teams compose powerful, safe and explainable AI capabilities — without wrestling with model minutiae or infra plumbing. You will design the agentic workflow framework, shared services such as memory, guardrails, vector search, SDKs and blueprints that translate foundation model power into production‑grade applications used by millions of users across multiple lines of businesses. In this role, you will: Partner with a cross‑functional team of engineers, research scientists, technical program managers, and product managers to deliver AI‑powered products that change how our associates work and how our customers interact with Capital One. Contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi‑tenant policy enforcement. Evaluate agentic frameworks such as LangGraph, AutoGen, Semantic Kernel, CrewAI and LlamaIndex, harden and blend patterns that meet enterprise SLAs so that 90% of new apps adopt them. Contribute to crafting an end‑to‑end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping‑to‑production timelines by 30%. Help bring together a vision of central guardrail services — prompt firewalls, content‑filter hooks, red‑team harnesses and audit APIs — consumed by every application to ensure zero Sev4 incidents. Collaborate with cross‑organization architects to drive end‑to‑end performance by optimizing orchestration – level batching, retrieval caching, heuristic tuning – to reduce per‑token spend. Accelerate innovation by incubating proof‑of‑concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. Own central Helm charts, operators and CRDs that auto‑scale agents to hit tenant SLAs. Coach and evangelize – hosting architecture office hours, mentoring staff, principal and senior engineers, authoring technical design documents and blogs and representing Capital One at Tier‑1 AI conferences to amplify platform vision across internal and external communities. Basic Qualifications Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies. At least 8 years of experience programming with Python, Go, Scala, or Java. Preferred Qualifications 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud). 2+ years of experience supporting agentic frameworks (LangChain, CrewAI, Semantic Kernel, or AutoGen). 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning). 8+ years of experience designing mission‑critical machine learning platforms. 2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems. Mandated ability to lead and mentor multiple engineering teams and influence cross‑functional stakeholders up to the VP level. Experience developing AI and ML algorithms or technologies (LLM inference, similarity search and vector databases, guardrails, memory) using Python, C++, C#, Java, or Golang. Master's degree in Computer Science, Computer Engineering, or a related technical field. Experience developing and applying state‑of‑the‑art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost. Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers. Experience leading GenAI or LLM‑powered application architectures in production. Deep understanding of Responsible AI, data privacy and multi‑tenant security patterns. Experience as a Staff‑plus or Distinguished IC engineer influencing 50+ engineers and C‑suite stakeholders. K8s mastery (multi‑region clusters, service mesh). Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production. 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