Sr. AI Engineer (GenAI Platform)

We are building responsible and reliable AI systems to transform banking for good. Our Intelligent Foundations and Experiences (IFX) team sits at the center of this mission, collaborating across the company to create proprietary AI platforms and solutions that serve millions of customers in safe, scalable, and high-impact ways. This role offers the opportunity to work on advanced AI infrastructure and production systems while contributing to meaningful product experiences. We offer a comprehensive and competitive benefits package, performance-based incentives, and compensation that varies by location, with roles available in locations such as Cambridge, McLean, New York, San Francisco, and San Jose. We also support eligible applicants with employment authorization sponsorship and are committed to an inclusive, equal-opportunity workplace.

- We require a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related discipline, plus at least 6 years of experience building AI and ML algorithms or technologies; alternatively, a masters degree in one of those fields plus at least 4 years of relevant experience.
- We require at least 6 years of programming experience with Python, Go, Scala, or Java.
- We prefer 7 years of experience delivering scalable, responsible AI solutions on cloud environments such as AWS, Google Cloud, Azure, or comparable private cloud platforms.
- We prefer experience architecting, integrating, delivering, and supporting complex AI systems.
- We prefer proven ability to lead and coach engineering teams while influencing cross-functional partners.
- We prefer hands-on experience developing AI and ML capabilities such as LLM inference, similarity search, vector databases, guardrails, or memory using Python, C++, C#, Java, or Golang.
- We prefer experience applying advanced methods to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
- We value strong technical depth in engineering, mathematics, hardware, software, and AI.
- We value a passion for staying current on AI research and translating new ideas into production.
- We value excellent communication and presentation skills, including the ability to explain complex AI topics clearly to peers.

- We partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how our associates work and how our customers engage with Capital One.
- We design, build, test, deploy, and support AI software components spanning foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- We use a broad mix of open-source and SaaS AI tools and platforms, including AWS Ultraclusters, Hugging Face, vector databases, NeMo Guardrails, PyTorch, and related technologies.
- We develop and introduce cutting-edge LLM optimization approaches to enhance scalability, cost efficiency, latency, and throughput for production AI systems.
- We help shape the technical direction and long-term roadmap for foundational AI systems across Capital One.
- We bring clarity to ambiguous technical problems, investigate root causes, and communicate findings and ideas with precision.