AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)
Capital One1 day ago
Cambridge, MA, USA +3 moreStaff+
Base Salary
$251k - $286k/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, evaluation, experimentation, governance, and observability components.
- Develop state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, throughput, and production performance.
- Design 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 ensure technical consistency and compliance with AI engineering standards.
- Mentor Principal- and Manager-level AI engineers and promote cross-domain technical learning.
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 such experience.
- At least six 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 seven or more years of experience.
- Experience designing, developing, delivering, and supporting complex AI systems.
- Experience with LLM inference, similarity search, vector databases, guardrails, memory, agentic AI systems, and agentic workflows.
- Experience optimizing training and inference software, hardware utilization, latency, throughput, cost, model compression, and dynamic inference strategies.
- Experience architecting unified production pipelines containing rule-based, retrieval-augmented, and generative components.
- Experience defining and enforcing ethical AI deployment standards involving explainability, fairness, and human-in-the-loop review.
- Experience right-sizing models, instance counts, and hardware types for requirements such as context length and token inputs and outputs.
- Strong understanding of engineering, mathematics, hardware, software, and AI, along with strong communication and presentation skills.
Benefits
- Comprehensive health, financial, and other benefits supporting employee well-being, with eligibility varying by work status and management level.
- Eligible for performance-based incentive compensation, including potential cash bonuses and/or long-term incentives.
- The role is expected to accept applications for a minimum of five business days.
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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.