This role pays more than
95%
of similar roles. Most pay
$163,600–$246,150
— the shaded band above.
At the midpoint, this role pays about
$306k
versus about
$205k
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.
Senior. Distinguished AI Engineer - Agentic AI Platform joins the Intelligent Foundations and Experiences team to build and deploy proprietary solutions that advance state-of-the-art science and engineering. This role involves developing a north star platform architecture, refining canonical APIs for agent orchestration, RAG pipelines, and prompt libraries while standardizing agentic workflows using frameworks like LangGraph, AutoGen, Semantic Kernel, CrewAI, and LlamaIndex. The engineer will build a GenAI SDK, CLI, and starter kits to accelerate development, alongside implementing guardrail services such as prompt firewalls and content-filter hooks. Technical requirements include proficiency in Python, Go, Scala, or Java, along with experience in LLMOps, Kubernetes, and vector databases. The role focuses on solving complex problems in banking by creating scalable, high-performance AI infrastructure to improve internal workflows and enhance customer interactions through automated, secure agentic systems.
What does a AI Engineer earn in California?
Median $246150 from 84 postings across 12 companies.
Develop and maintain core platform architecture including RAG pipelines, prompt libraries, and multi-tenant policy enforcement.
Evaluate and integrate agentic frameworks like LangGraph, AutoGen, and CrewAI to standardize enterprise workflows.
Build a comprehensive GenAI SDK, CLI, and starter kits to accelerate the transition from prototype to production.
Implement trust and safety guardrails including prompt firewalls, content filters, and red team harnesses.
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 agentic workflows.
Mentor senior engineering staff and represent the company at major AI conferences and internal technical forums.
What we're looking for
Bachelor's degree in Computer Science, Engineering, or AI with 10 years of experience developing AI/ML algorithms, or a Master's degree with 8 years of experience.
At least 10 years of experience programming with Python, Go, Scala, or Java.
9 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.
2+ years of experience architecting and delivering complex AI systems using Python, C++, C#, Java, or Golang.
Mastery of Kubernetes (K8s) for managing multi-region clusters and service meshes.
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
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Model Evaluation
Observability