AI Engineer: LLM & Fine-Tuning

Requirements:

• We require a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, along with at least 6 years of experience developing 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, CUDA, or Java.
• We prefer candidates with experience leading AI system development and making tradeoff decisions across cost, latency, throughput, and accuracy.
• We prefer 7 years of experience deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or comparable private cloud environments.
• We prefer experience designing, developing, delivering, and supporting complex AI systems.
• We prefer experience building AI and ML capabilities such as LLM inference, similarity search and vector databases, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• We prefer experience applying advanced techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
• We prefer experience building agentic AI systems and multi-agent workflows.
• We prefer a strong interest in the latest AI research and the ability to apply new techniques thoughtfully in production.
• We prefer excellent communication and presentation skills with the ability to explain complex AI concepts to peers.
• We prefer experience architecting and integrating heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into unified production pipelines.
• We prefer experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review.
• We prefer demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression.
• We prefer experience right-sizing models, instance counts, and hardware types based on requirements such as context length, token inputs, and token outputs.

Responsibilities:

• We will 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 interact with Capital One.
• We will design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• We will use a broad stack of open source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and related tools.
• We will invent and introduce advanced foundation model optimization techniques to improve scalability, cost, latency, and throughput in large-scale production AI systems.
• We will help shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
• We will design, implement, and optimize multi-model orchestration pipelines that combine LLMs, vector search, and domain-specific models into unified systems.
• We will establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
• We will lead design councils or design review boards to maintain technical consistency and alignment with AI engineering standards.
• We will mentor Principal- and Manager-level AI engineers and help strengthen cross-domain learning and organizational technical maturity.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• C#
• Cloud
• CUDA
• Golang
• Hardware
• Support
• Java
• LLM
• Model Training
• PyTorch
• Python
• Scala
• Machine Learning

More

We are Capital One, building responsible and reliable AI systems to change banking for good. Our Intelligent Foundations and Experiences (IFX) team sits at the center of our AI vision, partnering across the company to advance science and AI engineering while building proprietary solutions that create value for millions of customers. We operate at the intersection of AI models, platforms, and product experiences, delivering scalable and high-performance capabilities in a collaborative environment. This role includes location-based salary ranges for Cambridge, McLean, New York, San Francisco, and San Jose, as well as eligibility for performance-based incentives and a comprehensive benefits package focused on total well-being.

last updated 43 week of 2026