
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
At Capital One, we are creating responsible and reliable AI systems to change banking for good. For years, we have been an industry leader in using machine learning to create real-time, personalized customer experiences. 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 building world-class applied science and engineering teams to deliver industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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 partners across the company to advance the state of the art in science and AI engineering. 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.
As a Sr. Distinguished AI Engineer, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses. 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.
You will 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. A major emphasis is around standardizing and automating agentic workflows; you will evaluate frameworks such as LangGraph, AutoGen, Semantic Kernel, CrewAI, and LlamaIndex to harden and blend patterns that best meet enterprise SLAs. You will also craft an end-to-end GenAI SDK, CLI, and starter kits that let AI engineers spin up secure, observable agentic workflows in minutes, shrinking prototyping to production timelines.
Trust and safety remain paramount; you will help bring together a vision of central guardrail services—including prompt firewalls, content-filter hooks, red team harnesses, and audit APIs—consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross-organization architects to drive end-to-end performance by optimizing orchestration-level batching, retrieval caching, and heuristic tuning. Finally, you will coach and evangelize by hosting architecture office hours, mentoring Staff, Principal, and Senior engineers, authoring technical design documents, and representing Capital One at Tier 1 AI conferences.
You love to build systems, take pride in the quality of your work, and share our passion to do the right thing. You want to work on problems that will help change banking for good. You possess a passion for staying abreast of the latest research and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems, articulating your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown.
This role is expected to accept applications 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 in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws. If you require an accommodation to apply, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
Skills: Machine Learning, Agentic Frameworks, Langgraph, Autogen, Semantic Kernel, Crewai, Llamaindex, Genai SDK, Llmops, Vertex Ai.
Education: Bachelor's degree in Computer Science, Engineering, or AI required with 10+ years experience; Master's degree in Computer Science, Engineering, or relevant technical field preferred.
Work model: On-site
NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
New York, New York
9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. 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; demonstrated 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 (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang; Master's degree in Computer Science, Computer Engineering, or relevant 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; 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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