AI Engineer 4 (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory)
$197k - $225k • San Francisco, CA • Full-time
Posted 25d ago
About the job
At Capital One, we are building responsible and reliable AI systems to transform banking. Our team, Intelligent Foundations and Experiences (IFX), is at the forefront of this mission, developing and deploying proprietary AI solutions that impact millions of customers. We work with a cross-functional team to advance AI science and engineering, empowering other teams across the company to enhance their products with AI in responsible and scalable ways. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses.
Responsibilities
- Partner with cross-functional teams to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, and governance.
- Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance of large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems.
- Own the end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment.
- Define and maintain service-level objectives (SLOs) for AI reliability.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards.
- Mentor associates on scalable design, performance tuning, and research-to-production translation.
Requirements
- Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree plus at least 2 years of experience.
- At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.
- Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
- 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure).
- Experience designing, developing, delivering, and supporting AI services.
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software.
- Experience in building agentic AI systems and agentic workflows.
- Proficiency in designing distributed systems for model training, evaluation, and online inference.
- Experience defining AI model governance processes.
- Demonstrated ability to influence architectural decisions.