
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 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, building and deploying 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.
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.
In this role, 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 placed on standardizing and automating agentic workflows, evaluating frameworks like LangGraph and AutoGen to harden patterns that meet enterprise SLAs. You will also craft an end-to-end GenAI SDK and CLI to 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 to ensure zero Sev4 incidents. You will collaborate with cross-organization architects to drive end-to-end performance by optimizing orchestration and accelerating innovation by incubating proof of concepts. Finally, you will coach and evangelize, hosting architecture office hours, mentoring senior engineers, authoring technical design documents, and representing Capital One at Tier 1 AI conferences to amplify our platform vision across internal and external communities.
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 deep technical foundation in engineering and mathematics, enabling you to see and exploit optimization opportunities that others miss. You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown, adapting quickly to bring clarity to big, undefined problems.
This role is expected to accept applications for a minimum of 5 business days. We invite you to apply directly through our careers website. 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. We promote a drug-free workplace and consider for employment qualified applicants with a criminal history in a manner consistent with 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.
Recrutus helps candidates discover roles that match their skills and helps teams reach qualified applicants faster. Browse by metro, discipline, or work style — from internships to senior leadership.