This role pays more than
92%
of similar roles. Most pay
$162,000–$246,150
— the shaded band above.
At the midpoint, this role pays about
$288k
versus about
$204k
for comparable roles.
Based on 239 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
Distinguished AI Engineer - Agentic AI Platform joins the Intelligent Foundations and Experiences team to build an enterprise Generative AI Platform. This role focuses on designing agentic workflow frameworks, shared services like memory and guardrails, vector search, and SDKs to translate foundation model power into production-grade applications. You will develop RAG pipelines, prompt libraries, and multi-tenant policy enforcement while evaluating frameworks such as LangGraph, AutoGen, Semantic Kernel, CrewAI, and LlamaIndex. The role requires expertise in Python, Go, Scala, or Java, along with experience in LLMOps, Kubernetes, and cloud platforms like AWS, Google Cloud, or Azure. You will solve complex problems regarding agent orchestration, performance optimization, and trust and safety to ensure reliable AI systems. Additionally, you will mentor engineers, author technical designs, and advocate for the platform's vision across internal and external communities.
What does a AI Engineer earn in California?
Median $246150 from 84 postings across 12 companies.
Design agentic workflow frameworks including shared services for memory, guardrails, vector search, and SDKs.
Develop and refine platform architecture for RAG pipelines, prompt libraries, and multi-tenant policy enforcement.
Evaluate and harden agentic frameworks like LangGraph, AutoGen, and CrewAI to meet enterprise SLAs.
Build a comprehensive GenAI SDK, CLI, and starter kits to accelerate the transition from prototype to production.
Implement central guardrail services including prompt firewalls, content filters, and red team harnesses for safety.
Optimize orchestration performance through batching, retrieval caching, and heuristic tuning to reduce per-token costs.
Manage infrastructure components such as Helm charts, operators, and CRDs to auto-scale agents across tenants.
Mentor senior engineers and represent the company at major AI conferences to evangelize the platform vision.
What we're looking for
Bachelor's degree in Computer Science or Engineering plus 8 years of experience developing AI/ML algorithms, or a Master's degree plus 6 years of experience.
At least 8 years of experience programming with Python, Go, Scala, or Java.
8+ years of experience deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure.
8+ years of experience designing mission-critical machine learning platforms.
2+ years of experience supporting Agentic Frameworks such as LangChain, CrewAI, Semantic Kernel, or AutoGen.
2+ years of experience with LLMOps tools including Google Cloud Vertex AI, Amazon SageMaker, or Azure Machine Learning.
Experience architecting and delivering complex AI systems involving LLM inference, similarity search, vector databases, and guardrails.
Mastery of Kubernetes (K8s) for managing multi-region clusters and service meshes.