Full Stack Engineer, GenAI & Agentic Systems

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VARichmond, VAChicago, ILPlano, TXSan Francisco, CASan Jose, CANew York, NY
Salary: $179,400–$204,700 / yr
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $208k

This role $192k

$174k most similar roles pay here $231k

This role pays less than 65% of similar roles. Most pay $192,050–$223,750 — the shaded band above. At the midpoint, this role pays about $192k versus about $208k for comparable roles.

Based on 240 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 936 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 933 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Full Stack Engineer, GenAI & Agentic Systems

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Full Stack Engineer 4- People Tech- GenAI & Agentic Systems (LangChain, LangGraph) joins the People Tech team to drive digital transformation across corporate functions like HR and Legal. In this role, you will architect LLM-driven capabilities, design and deploy autonomous agentic AI solutions, and build multi-agent workflows to automate complex HR processes on an enterprise scale. You will lead a portfolio of projects involving distributed microservices while collaborating with security and risk teams to ensure compliant implementations. The technical stack includes Java, Scala, Python, Go, Node.js, JavaScript, and TypeScript, alongside RDBMS and NoSQL databases. You will utilize Docker, Kubernetes, and various AWS tools to build robust cloud-based solutions. Key technologies include LangChain, LangGraph, RAG architecture, vector databases, and CI/CD pipelines to solve complex business problems through innovative, scalable technology.

What does a Full Stack Engineer earn in Virginia?

Median $211200 from 149 postings across 4 companies.

See salary data

Skills

LangChain LangGraph LLM Python Java Go TypeScript JavaScript Node.js AWS GCP Azure Docker Kubernetes SQL NoSQL RAG Vector Databases CI/CD Infrastructure as Code Microservices

What you'll do

Architect LLM-driven capabilities and HRTech innovations to optimize enterprise-scale HR processes.
Design, build, and deploy autonomous agentic AI solutions and multi-agent workflows for global operations.
Ensure all AI-enabled capabilities are implemented in a secure, compliant, and well-managed manner with risk teams.
Lead a portfolio of distributed microservices and full-stack systems to meet corporate regulatory needs.
Provide technical leadership and set standards for design, development, and operational excellence across Agile teams.
Partner with architects to define service boundaries, integration patterns, and reusable AI execution frameworks.
Identify areas for improvement by performing targeted refactoring to reduce technical debt and improve performance.
Influence long-term technology strategy through the evaluation of emerging tools and practices in a "you build it, you own it" environment.

What we're looking for

Bachelor's Degree or higher in Computer Science or a related quantitative field.
At least 4 years of experience in software engineering.
At least 2 years of experience with public cloud platforms, cloud-based productivity tools, or virtualization technologies.
Master’s Degree in Computer Science or a related field (preferred).
7+ years of experience in coding with more than two of Python, Java, JavaScript, TypeScript, SQL, or Go (preferred).
3+ years of experience with database and database management systems (preferred).
4+ years of experience contributing to open source frameworks (preferred).
Experience with RAG architecture, vector databases, or agentic LLM pipeline design using LangGraph or LangChain (preferred).

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