AI Engineer (Gen AI Platform Services)

Salary: $197,300 - 245,600 per year Requirements: We require a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related discipline plus at least 4 years of experience developing AI and ML algorithms or technologies, or a masters degree in one of those fields plus at least 2 years of experience developing AI and ML algorithms or technologies. We require at least 4 years of experience programming in Python, Go, Scala, CUDA, or Java. We prefer experience leading the development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy. We prefer 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud. We prefer experience designing, developing, delivering, and supporting AI services. We prefer experience building 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. 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 agentic workflows. We prefer strong awareness of current AI research and systems, with the ability to apply new techniques thoughtfully in production. We prefer proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale. We prefer experience defining AI model governance processes, including reproducibility, lineage tracking, and automated retraining schedules. We prefer demonstrated ability to influence architectural decisions across multiple AI product lines or platforms. Responsibilities: We 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 engage with us. We 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 use a broad range of open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and similar tools. We invent and apply state-of-the-art foundation model optimization approaches to improve scalability, cost, latency, and throughput in large-scale production AI systems. We help shape the technical vision and long-term roadmap for foundational AI systems. We own end-to-end architecture for complex AI systems, with attention to maintainability, observability, and ethical alignment. We define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift. We work with infrastructure engineering to improve GPU and TPU utilization and speed up model inference pipelines. We lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are satisfied. We mentor Principal and Senior Associates on scalable design, performance tuning, and translating research into production. Technologies: Agentic AI AI AWS Azure C# Cloud CUDA Golang Hardware Support Java LLM Model Training PyTorch Python Scala Security Machine Learning More: At Capital One, we are building responsible and reliable AI systems to help change banking for good. Our Intelligent Foundations and Experiences team sits at the center of our AI vision, partnering across the company to advance science and AI engineering and to deliver proprietary solutions that serve millions of customers. We build scalable, high-performance AI platforms that help teams enhance products in responsible ways. This role is based in locations including Cambridge, McLean, New York, San Francisco, and San Jose, with salary ranges varying by location, and it is also eligible for performance-based incentives and a comprehensive benefits package supporting total well-being. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. last updated 38 week of 2026