AI Engineer 5 (Gen AI Platform Services - Agentic Systems)
Capital One2 days 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 AI software components including foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Optimize foundation models and production AI systems for scalability, cost, latency, throughput, and hardware utilization.
- Design and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
- Lead cost-performance governance reviews tracking 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 maintain technical consistency and AI engineering standards.
- Mentor Principal- and Manager-level AI engineers and improve organizational technical maturity.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 6 years of experience developing AI and ML algorithms or technologies, or a relevant master's degree plus at least 4 years of such experience.
- At least 6 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 experience deploying scalable and responsible AI solutions on cloud platforms, including 7 years of experience preferred.
- Experience designing, developing, delivering, and supporting complex AI systems.
- Experience with LLM inference, similarity search, VectorDBs, guardrails, and memory using languages such as Python, C++, C#, Java, CUDA, or Golang.
- Experience optimizing training and inference software and applying state-of-the-art techniques to improve hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and agentic workflows.
- Experience architecting heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into unified production pipelines.
- Experience defining and enforcing ethical AI deployment standards involving explainability, fairness, and human-in-the-loop review.
- Ability to balance 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.
- Strong communication and presentation skills, with the ability to explain complex AI concepts.
Benefits
- Capital One offers comprehensive health, financial, and other benefits supporting employee well-being, with eligibility varying by employment and management status.
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.