AI Engineer 4 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)
Capital One1 day ago
Cambridge, MA, USA +3 moreStaff+
Base Salary
$197k - $246k/yr
Responsibilities
- Partner with cross-functional engineering, research, program management, and product teams to deliver AI-powered products.
- Design, develop, test, deploy, and support foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability components.
- Optimize foundation models and production AI systems for scalability, cost, latency, throughput, and hardware utilization.
- Own end-to-end architecture for complex AI systems and contribute to the long-term technical roadmap for foundational AI systems.
- Define and maintain AI reliability SLOs covering latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and model inference pipelines.
- Lead technical reviews for AI deployments while ensuring security, data governance, compliance, and ethical standards.
- 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 a related field plus at least four years of experience developing AI and ML algorithms or technologies, or a relevant master’s degree 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 tradeoff decisions involving cost, latency, throughput, and accuracy.
- Preferred: six or more years deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
- Preferred experience developing AI services, LLM inference, similarity search, VectorDBs, guardrails, memory, agentic AI systems, and agentic workflows.
- Preferred experience optimizing training and inference software for hardware utilization, latency, throughput, and cost.
- Preferred proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Preferred experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules.
- Preferred ability to influence architectural decisions across multiple AI product lines or platforms.
Benefits
- Capital One offers comprehensive health, financial, and other benefits supporting employees’ total well-being, with eligibility varying by employment status and management level.
- The role is eligible for performance-based incentive compensation, including potential cash bonuses and long-term incentives.
- The role is posted for work in locations including Cambridge, McLean, New York, San Francisco, and San Jose, with location-specific annual salary ranges.
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.