AI Engineer 5

Capital One • McLean, NY

3d

About The Position

Capital One is hiring an AI Engineer 5 for its Intelligent Foundations and Experiences (IFX) team. The team partners across the company to advance AI science and engineering and to build and deploy proprietary solutions that support business needs and millions of customers. Its AI models and platforms help teams deliver AI-powered products responsibly and at scale.

In this role, you will work with engineers, research scientists, technical program managers, and product managers to build AI products for associates and customers. You will develop and support foundational AI systems and production software, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability. You will also develop optimization techniques, orchestration pipelines, and cost-performance governance practices, and contribute to the technical vision and roadmap for Capital One's foundational AI systems.

The role calls for a deeply technical, resilient engineer who can apply current AI research judiciously, make sound engineering tradeoffs, and bring clarity to complex or undefined problems. It includes technical leadership through design reviews and councils, mentoring senior AI engineers, and promoting consistent engineering standards.

Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 6 years of experience developing AI and ML algorithms or technologies; or a master's degree in one of these fields and at least 4 years of such experience.
• At least 6 years of programming experience with Python, Go, Scala, CUDA, or Java.

Nice To Haves

• Experience leading development of AI systems and making tradeoff decisions involving cost, latency, throughput, and accuracy.
• 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Experience designing, developing, delivering, and supporting complex AI systems.
• Experience developing AI and ML algorithms or technologies, such as LLM inference, similarity search and vector databases, guardrails, and memory, using Python, C++, C#, Java, CUDA, or Golang.
• Experience developing and applying state-of-the-art techniques to optimize training and inference software, hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and workflows.
• Interest in current AI research and systems, and ability to apply novel techniques judiciously in production.
• Excellent communication and presentation skills, including the ability to explain complex AI concepts to peers.
• Experience architecting and integrating rule-based, retrieval-augmented, and generative AI components into unified production pipelines.
• Experience defining and enforcing ethical AI deployment standards, including explainability, fairness, and human-in-the-loop review processes.
• Ability to balance model performance and operational cost using dynamic inference strategies and model compression.
• Experience right-sizing models, instance counts, and hardware types to meet requirements such as context length and token inputs and outputs.

Responsibilities

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
• Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agent 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 foundation-model optimization techniques to improve production AI system scalability, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
• Establish and lead cost-performance governance reviews, tracking GPU utilization, model throughput, and inference cost efficiency.
• Lead team design councils or design review boards to support technical consistency and compliance with AI engineering standards.
• Mentor Principal- and Manager-level AI engineers, fostering cross-domain learning and improving organizational technical maturity.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior