AI Engineer 4 (AI Foundations, VLM Customization)
About The Position
Capital One’s Intelligent Foundations and Experiences (IFX) team builds and deploys proprietary AI models and platforms that enable teams across the company to deliver responsible, scalable AI capabilities. The AI Engineer 4 partners with engineers, research scientists, technical program managers, and product managers to create AI-powered products for associates and customers. The role designs, develops, tests, deploys, and supports AI software components, including foundation-model training, large-language-model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It uses open-source and SaaS AI technologies and develops optimization techniques to improve the scalability, cost, latency, and throughput of production AI systems. The engineer contributes to the technical vision and long-term roadmap for foundational AI systems, owns architecture for complex AI systems, and helps ensure systems are maintainable, observable, and ethically aligned. The position also defines reliability objectives, collaborates on GPU/TPU utilization and inference pipelines, leads technical reviews addressing security, data governance, and compliance, and mentors Principal and Senior Associates.
Requirements
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 4 years of experience developing AI and ML algorithms or technologies; alternatively, a master’s degree in one of these fields and at least 2 years of that experience.
- At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
Nice To Haves
- Experience leading AI system development and making tradeoff decisions involving cost, latency, throughput, and accuracy.
- 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
- Experience designing, developing, delivering, and supporting AI services.
- Experience developing AI and ML algorithms or technologies, such as LLM inference, similarity search and vector databases, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and workflows.
- Interest in keeping current with AI research and systems and applying novel techniques in production.
- Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
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, agent and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Use open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch.
- Develop foundation-model optimization techniques that improve production AI system scalability, cost, latency, and throughput.
- Contribute to the technical vision and long-term roadmap for foundational AI systems.
- Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment.
- Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead cross-functional technical reviews for AI deployments to ensure security, data governance, and compliance standards are met.
- Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.
- Performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
