AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)
Capital One1 day ago
Cambridge, MA, USA +4 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 AI components for foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability.
- Use open-source and SaaS AI technologies to build scalable production AI systems.
- Develop foundation model optimization techniques improving scalability, cost, latency, throughput, and hardware utilization.
- Own end-to-end architecture and contribute to the technical vision and roadmap for foundational AI systems.
- 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 covering security, data governance, and compliance.
- 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 master's degree in one of these fields plus at least 2 years of relevant experience.
- At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
- Strong engineering, mathematics, hardware, software, and AI foundations.
- Preferred experience leading AI system development with cost, latency, throughput, and accuracy tradeoffs.
- Preferred 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
- Experience developing, delivering, and supporting AI services, including LLM inference, similarity search, VectorDBs, guardrails, and memory.
- Experience optimizing training and inference software and improving hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and workflows.
- Experience designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, lineage tracking, and automated retraining schedules.
- Demonstrated ability to influence architecture across multiple AI product lines or platforms.
Benefits
- Comprehensive health, financial, and other benefits supporting employee well-being; eligibility varies by employment status and management level.
- The role is eligible for performance-based incentive compensation, including potential cash bonuses and/or long-term incentives.
- 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.