AI Engineer 5 (AI Foundations)
Capital One1 day ago
Cambridge, MA, USA +3 moreStaff+
Base Salary
$230k - $286k/yr
Responsibilities
- Design, develop, test, deploy, and support AI software components for foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, governance, and observability.
- Invent and apply foundation model optimization techniques to improve scalability, cost, latency, throughput, and hardware utilization.
- Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
- Lead cost-performance governance reviews covering GPU utilization, model throughput, and inference cost efficiency.
- Contribute to the technical vision and long-term roadmap for foundational AI systems.
- Lead design councils and review boards to promote technical consistency and compliance with AI engineering standards.
- Mentor Principal- and Manager-level AI engineers and elevate organizational technical maturity.
- Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least six years of experience developing AI and ML algorithms or technologies, or a master's degree in one of these fields plus at least four years of relevant experience.
- At least six years of programming experience with Python, Go, Scala, CUDA, or Java.
- Experience leading AI system development with tradeoffs among cost, latency, throughput, and accuracy.
- Preferred experience deploying scalable and responsible AI solutions on cloud platforms, including seven or more years of such experience.
- Experience developing complex AI systems, AI and ML algorithms, LLM inference, similarity search, vector databases, guardrails, and memory systems.
- Experience optimizing training and inference software and improving hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and workflows.
- Experience architecting heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into unified production pipelines.
- Experience defining ethical AI deployment standards covering explainability, fairness, and human-in-the-loop review.
- Experience balancing model performance and operational cost through dynamic inference strategies and model compression.
- Experience right-sizing models, instance counts, and hardware types based on requirements such as context length and token inputs and outputs.
- Excellent communication and presentation skills, with the ability to explain complex AI concepts.
- Strong engineering, mathematics, hardware, software, and AI expertise and the ability to apply current AI research in production.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being, with eligibility varying by full-time or part-time status, exempt or non-exempt status, and management level.
- Performance-based incentive compensation may include cash bonuses and/or long-term incentives.
- The role is offered across listed locations including Cambridge, McLean, New York, and San Jose, 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.