Lead AI Engineer (FM Hosting, LLM Inference)

Overview 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. 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. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state‑of‑the‑art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large‑scale production AI systems. Contribute to the technical vision and the long‑term roadmap of foundational AI systems at Capital One. The Ideal Candidate You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. 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 and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables 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. Basic Qualifications Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies. At least 4 years of experience programming with Python, Go, Scala, or Java. Preferred Qualifications 6 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 AI services. 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. Experience developing and applying state‑of‑the‑art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production. Compensation & Benefits Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. CapitalOne promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; SanFrancisco, California Police Code Article 49, Sections4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. For technical support or questions about CapitalOne’s recruiting process, please send an email to View email address on click.appcast.io. #J-18808-Ljbffr