AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)
Capital One2 days ago
Cambridge, MA, USA +2 moreStaff+
Base Salary
$215k - $246k/yr
Responsibilities
- Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
- Design, develop, test, deploy, and support foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability components.
- Develop optimization techniques for the scalability, cost, latency, throughput, and performance of production AI systems.
- Own end-to-end architecture for complex AI systems and contribute to the long-term roadmap for 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 model inference pipelines.
- Lead technical reviews for AI deployments, including security, data governance, and compliance considerations.
- 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 4 years of experience developing AI and ML algorithms or technologies, or a relevant master's degree plus at least 2 years of that experience.
- At least 4 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: 6 years of experience deploying scalable and responsible AI solutions on AWS, Google Cloud, Azure, or an equivalent private cloud.
- Preferred: experience developing AI services, LLM inference, similarity search, vector databases, guardrails, memory systems, agentic AI, 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 lineage tracking and automated retraining schedules.
- Preferred: demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being, with eligibility varying by employment status and management level.
- Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
- Role is available in Cambridge, MA; McLean, VA; New York, NY; and San Jose, CA, with location-specific salary ranges.
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.