This role pays more than
99%
of similar roles. Most pay
$180,687–$221,100
— the shaded band above.
At the midpoint, this role pays about
$268k
versus about
$201k
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.
The Senior Lead Software Engineer, Full Stack (Enterprise Platform Technology) joins the AI Harness Engineering team to build tools, contracts, evaluation systems, and release controls for governed AI-native software delivery. This role involves leading a portfolio of projects and a team of developers to create agentic workflow orchestration systems, typed input/output contracts, and observability capabilities for AI-assisted engineering workflows. The position focuses on building reusable APIs, services, and developer tooling while ensuring compliance with regulatory needs. Key technologies include JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, alongside Open Source RDBMS and NoSQL databases. The role also utilizes Docker, Kubernetes, and various AWS tools to develop cloud-based solutions. The work centers on the technical challenge of integrating LLM APIs and generative models into production environments while maintaining enterprise-grade quality, security, and auditability.
Lead a portfolio of diverse technology projects and a team of developers to create solutions meeting regulatory needs.
Design and implement AI-native software engineering harnesses using approved models, coding agents, and governed control-plane capabilities.
Build agentic workflow orchestration systems that support planning, code generation, validation, and controlled promotion through delivery environments.
Define and implement typed input/output contracts and metadata capture to ensure agentic execution is auditable and repeatable.
Develop trace capture, observability, and debugging capabilities for AI-assisted engineering workflows including prompt lineage and failure analysis.
Integrate evaluation results into CI/CD pipelines with quality gates for security, performance, and human-review outcomes.
Build reusable APIs, services, and developer tooling to enable consistent adoption of AI-native engineering practices.
Write architecture proposals, design documents, and technical guidance to scale harness engineering patterns across the organization.
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).
9+ years of experience in at least one of the following: JavaScript, Java, TypeScript, SQL, Python, or Go.
4+ years of experience with open-source frameworks to build production-grade applications.
4+ years of experience with cloud-native architectures, microservices, APIs, containers, Kubernetes, serverless platforms, or event-driven systems.
2+ years of experience with CI/CD, automated testing, quality gates, developer productivity platforms, or observability frameworks.