AI Engineer 4 (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory)
Capital One1 day ago
Cambridge, MA, USA +4 moreStaff+
Base Salary
$215k - $246k/yr
Responsibilities
- Design, develop, test, deploy, and support AI software components for model training, LLM inference, agentic and multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability.
- Develop optimization techniques for large-scale production AI systems to improve scalability, cost, latency, throughput, and hardware utilization.
- Own end-to-end architecture for complex AI systems and contribute to the technical vision and roadmap of foundational AI platforms.
- Define and maintain AI reliability objectives covering latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead technical reviews for AI system deployments while ensuring security, data governance, compliance, maintainability, observability, and ethical alignment.
- Mentor Principal and Senior Associates on scalable design, performance tuning, and translating research into production.
Requirements
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least four years of experience developing AI and ML algorithms or technologies, or a master’s degree in one of these fields plus at least two years of such experience.
- At least four years of programming experience with Python, Go, Scala, CUDA, or Java.
- Experience leading AI system development with tradeoffs involving cost, latency, throughput, and accuracy.
- Preferred experience deploying scalable and responsible AI solutions on AWS, Google Cloud, Azure, or equivalent private cloud environments, including six or more years of experience.
- Experience designing, developing, delivering, and supporting AI services and developing AI/ML technologies such as LLM inference, similarity search, VectorDBs, guardrails, and memory.
- Experience optimizing training and inference software and building agentic AI systems and workflows.
- Experience 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 retraining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
- Experience with Python, C++, C#, Java, CUDA, or Go and the ability to apply current AI research techniques in production.
Benefits
- Capital One offers comprehensive health, financial, and other benefits supporting employee well-being, with eligibility varying by employment status and management level.
- The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
- The position is expected to accept applications for a minimum of five business days.
Categories
About Capital One
Capital One is a U.S. consumer and commercial bank that offers credit cards, checking and savings accounts, auto financing, and lending to small and large businesses. It earns revenue from interest income and interchange/fees across its card and banking products, and develops cloud-based digital services. Founded in 1994, Capital One is publicly traded on the NYSE (COF) and is headquartered in McLean, Virginia.