Senior Lead Software Engineer, Full Stack (AI Platform & Knowledge Library) (Enterprise Platforms Technology)

Capital One Financial

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: New York, NYMcLean, VARichmond, VA
Salary: $229,900–$262,400 / yr
Posted: 39 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k

This role $246k

$139k most similar roles pay here $276k

This role pays more than 96% of similar roles. Most pay $152,131–$222,812 — the shaded band above. At the midpoint, this role pays about $246k versus about $187k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Senior Lead Software Engineer, Full Stack (AI Platform & Knowledge Library) (Enterprise Platforms Technology)

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Senior Lead Software Engineer, Full Stack (AI Platform & Knowledge Library) (Enterprise Platforms Technology) joins the Enterprise Platforms Technology team to own the AI platform and knowledge infrastructure for marketing content generation. This role involves building a RAG-backed Content Moderation Knowledge Library covering regulatory requirements and brand rules, while managing the embedding search pipeline including chunking strategies and hybrid search. The engineer will lead Prompt MLOps by treating prompts as versioned artifacts, manage shared API contracts, and design agentic critic validation streams for compliance and brand voice. Key technical requirements include Python, cloud computing experience with AWS services like S3, Lambda, and OpenSearch, and expertise in vector search infrastructure such as Pinecone or Weaviate. The role solves the complex problem of ensuring AI-generated content remains compliant and on-brand across multiple channels through robust production software systems.

Skills

Python RAG LLM AWS OpenSearch Pinecone PGvector Weaviate S3 Lambda SQS Prompt MLOps Vector Search Machine Learning AI Platform Knowledge Engineering

What you'll do

Build a RAG-backed Content Moderation Knowledge Library covering regulatory requirements and brand rules.
Implement and tune embedding search pipelines including chunking strategies, model selection, and hybrid search.
Manage Prompt MLOps by treating prompts as versioned artifacts and maintaining an evaluation loop for quality.
Develop and manage shared API contracts for AI content compliance and generation across multiple engineering teams.
Design an agentic critic validation stream using both deterministic rules and LLM-as-judge semantic validators.
Lead technical designs, produce architecture documents, and conduct design reviews for RAG systems.
Mentor engineers on evaluation methodologies, production AI operations, and RAG system design.

What we're looking for

At least 6 years of experience in software engineering.
At least 1 year of experience with cloud computing (AWS, Microsoft Azure, or Google Cloud).
4+ years of experience in Python.
4+ years of experience building and operating retrieval-augmented generation (RAG) systems.
3+ years of experience in applied AI/ML or LLM-based systems in production.
3+ years of experience with vector search infrastructure such as OpenSearch, Pinecone, PGvector, or Weaviate.
3+ years of experience designing and owning shared platform APIs.
Bachelor’s Degree.

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