Director, Full-stack Engineer

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Plano, TX
Salary
$244,700–$279,200 / yr
Employment
Full-time
Posted
14 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $229k
This role $262k
$187k $289k
below market most similar roles pay here above market

This role pays more than 87% of similar roles. Most pay $211,200–$246,150 — the blue band above. At the midpoint, this role pays about $262k versus about $229k 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 1917 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1045 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Director, Full-stack Engineer

Director, Full-stack Engineer leads high-performing engineering teams to develop a core in-house application providing real-time guidance for sales associates during client calls. This role involves managing multiple product-focused software engineers, mentoring staff, and driving engineering strategy to deliver scalable, customer-centric solutions. Key responsibilities include overseeing the transition from monolithic applications to microservice architectures, defining long-term technical roadmaps, and ensuring system resilience. The position requires expertise in AWS, data architecture, and enterprise design patterns. Candidates must possess hands-on experience with AI-enabled products, including Retrieval-Augmented Generation (RAG) models, LLMs, and generative AI tools. Technical proficiency in Go, Java, JavaScript, TypeScript, Python, Rust, and C# is required to build modern full-stack applications that integrate complex data consumption patterns and real-time intelligent guidance systems.

What you'll do

  • Lead and grow multiple teams of product-focused software engineers to deliver scalable, customer-centric solutions.
  • Architect and build AI-enabled products using generative AI, LLMs, and Retrieval-Augmented Generation (RAG) models.
  • Oversee the migration of monolithic applications into microservice architectures and deploy them into AWS environments.
  • Define long-term technical strategy, architecture standards, and platform roadmaps for enterprise-level systems.
  • Mentor engineers and managers to drive professional development, succession planning, and technical excellence.
  • Partner with product managers and executive leaders to align technology capabilities with business goals.
  • Ensure the craftsmanship, availability, resilience, and scalability of all production-grade full-stack applications.
  • Drive talent strategy by recruiting top-tier engineers and fostering a culture of continuous learning.

What we're looking for

  • Bachelor's Degree or higher in Computer Science or a related quantitative field.
  • At least 5 years of people management experience.
  • At least 7 years of experience in software engineering, solution architecture, enterprise architecture, cloud computing, and data architecture.
  • Master’s Degree in Computer Science or Software Engineering (preferred).
  • 10+ years of experience in software engineering, solution architecture, enterprise architecture, web technologies, cloud computing, and data architecture (preferred).
  • 10+ years of professional experience coding in languages like Go, Java, JavaScript/TypeScript, Python, Rust, C#, or Scala (preferred).
  • 2+ years of experience designing and deploying production-grade AI-enabled applications, including RAG models and data consumption patterns (preferred).
  • 3+ years of experience building and scaling full-stack applications leveraging generative AI, LLMs, and event-driven data architectures (preferred).

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