AI Engineer 4 (AI Foundations: Benchmarking, Evaluation, and Explainability)
Job Description
Capital One is hiring an AI Engineer 4 for the Intelligent Foundations and Experiences (IFX) team in New York, NY (onsite).
Responsibilities
- Work with cross-functional partners across engineering, research science, technical program management, and product management to deliver AI-powered products
- Design, develop, test, deploy, and support AI software components, including:
- Foundation model training
- LLM inference
- Agents and multi-agent workflows
- Similarity search and VectorDB-based retrieval
- Guardrails
- Model evaluation, experimentation, governance, and observability
- Apply Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more
- Develop state-of-the-art foundation model optimization techniques to improve production metrics including scalability, cost, latency, and throughput
- Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One
- Own end-to-end architecture for complex AI systems with a focus on maintainability, observability, and ethical alignment
- Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift
- Partner with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
- Lead cross-functional technical reviews for new AI deployments, ensuring security, data governance, and compliance standards are met
- Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation
Requirements
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4+ years experience developing AI/ML algorithms or technologies
- OR Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2+ years experience developing AI/ML algorithms or technologies
- 4+ years programming experience with Python, Go, Scala, CUDA, or Java
Technologies
- AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
- AWS, Google Cloud, Azure
- Python, Go, Scala, CUDA, Java, C++, C#, Golang
- GPU, TPU
Benefits
- Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being
- Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI)
Team: Intelligent Foundations and Experiences (IFX)
- Central to bringing Capital One’s AI vision to life
- Collaborates across the company to advance science and AI engineering, and builds/deploys proprietary solutions that deliver value to millions of customers
- Builds AI models and platforms enabling teams to enhance products with responsible and scalable AI
Preferred Qualifications
- Experience leading development of AI systems with tradeoffs across cost, latency, throughput, and accuracy
- 6+ years 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, CUDA, or Golang
- Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost
- Experience building agentic AI systems and agentic workflows
- Demonstrated ability to design distributed systems for model training, evaluation, and online inference at petabyte scale
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retention schedules
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms