AI Engineer (MLXT)

Requirements:

• Bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 6 years of experience developing AI/ML algorithms or technologies; or a relevant masters degree plus at least 4 years of such experience.
• At least 6 years of programming experience with Python, Go, Scala, CUDA, or Java.
• Strong engineering and mathematics fundamentals, with technical expertise across hardware, software, and AI.
• Ability to interpret AI research and apply suitable techniques in production; adapt to ambiguous problems, investigate root causes, communicate findings clearly, and develop solutions to unfamiliar challenges.
• Preferred: Experience leading AI system development and making cost, latency, throughput, and accuracy trade-offs.
• Preferred: 7 or more years deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud environments.
• Preferred: Experience designing, building, delivering, and supporting complex AI systems, including LLM inference, similarity search, vector databases, guardrails, or memory.
• Preferred: Experience with AI/ML development using Python, C++, C#, Java, CUDA, or Golang, and with optimization techniques that improve hardware utilization, latency, throughput, or cost.
• Preferred: Experience building agentic AI systems and workflows, and architecting unified production pipelines that integrate rule-based, retrieval-augmented, and generative systems.
• Preferred: Experience setting ethical AI deployment standards, including explainability, fairness, and human-in-the-loop review; balancing performance and operating costs through dynamic inference or model compression; and right-sizing models, instances, and hardware for workload needs.
• Preferred: Strong communication and presentation skills, including the ability to explain complex AI concepts to peers, and an interest in keeping current with AI research and systems.

Responsibilities:

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for our associates and customers.
• Design, develop, test, deploy, and support AI components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Use open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch.
• Develop and introduce foundation-model optimization techniques to improve the scalability, cost, latency, and throughput of production AI systems.
• Help shape the technical vision and long-term roadmap for our foundational AI systems.
• Design, implement, and optimize multi-model orchestration pipelines that combine LLMs, vector search, and domain-specific models.
• Establish and lead cost-performance governance reviews, monitoring GPU utilization, model throughput, and inference cost efficiency.
• Lead design councils or review boards to support technical consistency and adherence to AI engineering standards.
• Mentor Principal- and Manager-level AI engineers, encouraging cross-domain learning and strengthening organizational technical capabilities.

Technologies:

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

More

At Capital One, we build responsible, reliable AI systems to improve banking and create personalized customer experiences. Our Intelligent Foundations and Experiences team works across the company to advance AI science and engineering and develop proprietary models and platforms used by teams serving millions of customers. We offer this AI Engineer 5 role in Cambridge, Massachusetts; McLean, Virginia; New York, New York; San Francisco, California; and San Jose, California. Listed annual salary ranges are $229,900–$262,400 in Cambridge and McLean, and $250,800–$286,200 in New York, San Francisco, and San Jose; pay for other locations varies. The role is also eligible for performance-based incentives. We provide a competitive, inclusive benefits package supporting health and overall well-being, with eligibility dependent on role and employment status. We are an equal opportunity employer and will consider sponsoring a new qualified applicant for employment authorization for this position.

last updated 43 week of 2026