AI Engineer 4
$197k - $225k • New York, NY • Full-time
Posted 1mo ago
About the job
Capital One is seeking an AI Engineer to join the Intelligent Foundations and Experiences (IFX) team. This role involves building and deploying proprietary AI solutions that are central to the business and deliver value to millions of customers. You will partner with a cross-functional team to deliver AI-powered products that change how associates work and how customers interact with Capital One. The position focuses on advancing the state of the art in AI engineering and building scalable, high-performance AI infrastructure to reimagine banking services.
Responsibilities
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems.
- Own the end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment.
- Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met.
- Mentor 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 at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies.
- At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.
- Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
- 6 years of experience 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 developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Experience in building agentic AI systems and agentic workflows.
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production.
- Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.