Senior Lead Software Engineer, Full Stack; Enterprise Platform Technology

Position: Senior Lead Software Engineer, Full Stack (Enterprise Platform Technology)
Location: New York

Senior Lead Software Engineer, Full Stack (Enterprise Platform Technology)

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs. We are seeking Full Stack Software Engineers who are passionate about marrying data with emerging technologies.

As a Capital One Senior Lead Software Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within Capital One.

Who We Are

Capital One's Enterprise Platforms Technology builds and operates many of Capital One's most important enterprise platforms. We establish engineering practices, reusable platform capabilities, and production-ready patterns that help teams deliver reliable, secure, and scalable technology solutions across the company. The AI Harness Engineering team is focused on enabling governed AI-native software delivery. We build the tools, contracts, evaluation systems, and release controls that allow engineering teams to use approved AI models and coding agents with enterprise-grade quality, traceability, and operational discipline.

What You'll Do:

• Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices and full-stack systems to create solutions that help meet regulatory needs for the company
• Lead the design and implementation of AI-native software engineering harnesses that use approved models, coding agents, and developer workflows in governed control-plane capabilities
• Build agentic workflow orchestration systems that support planning, code generation, validation, retry loops, human checkpoints, and controlled promotion through delivery environments
• Define and implement typed input/output contracts, schemas, metadata capture, and workflow state models that make agentic execution auditable and repeatable
• Develop trace capture, observability, and debugging capabilities for AI-assisted engineering workflows, including prompt/output lineage, tool-call traces, model/runtime metadata, and failure analysis
• Integrate evaluation results into CI/CD and release workflows, including quality gates for fidelity, build correctness, accessibility, security, performance, and human-review outcomes
• Build reusable APIs, services, developer tooling, dashboards, and reference implementations that enable teams to adopt AI-native engineering practices consistently
• Utilize programming languages like JavaScript, Java, HTML/CSS, Type Script, SQL, Python, and Go, Open Source RDBMS and No
  
  SQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services
• Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
• Partner with application teams to migrate complex software and digital experiences using governed agentic workflows, while preserving engineering quality, customer experience, and enterprise controls
• Collaborate with Cyber, Risk, Responsible AI, Architecture, Product, and Platform teams to ensure solutions meet enterprise standards for security, auditability, compliance, and operational readiness
• Write architecture proposals, design documents, runbooks, and technical guidance that help scale harness engineering patterns across teams
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community, and from time to time, be asked to code or evaluate code

Basic Qualifications:

• Bachelor's Degree
• At least 6 years of experience in software engineering (Internship experience does not apply)
• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications:

• Master's Degree
• 9+ years of experience in at least one of the following:
  JavaScript, Java, Type Script, SQL, Python, or Go
• 4+ years of experience utilizing 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 using AWS, Google Cloud Platform, or Microsoft Azure.
• 2+ years of experience with CI/CD, automated testing, quality gates, developer productivity platforms, or observability frameworks (such as Open Telemetry for logging, metrics, tracing, and dashboards).
• 2+ years of experience working within an Agile delivery environment utilizing Agile practices and frameworks.
• 1+ years of experience integrating LLM APIs, building application workflows around generative models, or deploying AI-assisted developer tools into production or enterprise software workflows.
• 1+ years of…