Full Stack Engineer 5 - Global Workforce Services - AI Automation

Capital One • McLean, VA

23h • $209,000 - $238,500

About The Position

Capital One is seeking a Full Stack Engineer for Global Workforce Services, the engineering team that powers enterprise facilities and physical security across SaaS, COTS, and custom applications. The team supports a footprint of more than 10,000 IoT devices and is transforming IoT management and software delivery using AI, autonomous agents, and retrieval-augmented generation (RAG) pipelines.

The role leads technology projects and developers in building distributed microservices and full-stack systems that address company needs, including regulatory requirements. It combines frontend development of responsive web and real-time AI chat interfaces with backend services, APIs, and integrations connecting AI agents to enterprise systems, databases, third-party APIs, and legacy software. The engineer will architect and integrate rule-based, retrieval-augmented, and generative AI components into production pipelines.

The position provides technical leadership across teams, drives the design and implementation of large-scale distributed and cloud-native systems, and partners with architects and product leaders on platform roadmaps and shared services strategy. It also involves collaboration with digital product managers, mentoring engineers, and contributing to technology communities and the ongoing development of robust cloud-based solutions.

Requirements

• Bachelor's degree or higher in Computer Science or a related quantitative field, such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
• At least 6 years of software engineering experience; internship experience does not count.
• At least 3 years of experience with public cloud platforms (AWS, GCP, or Azure), cloud-based productivity tools, or virtualization technologies.

Nice To Haves

• Master's degree in Computer Science or a related field.
• 2+ years of experience building production RAG pipelines, including chunking, embeddings, vector indexing, graph RAG, or fine-tuning.
• 2+ years of experience with agentic patterns such as tool calling, ReAct loops, Plan-and-Execute, or multi-agent collaboration.
• 2+ years of experience with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel, and model APIs such as OpenAI, Anthropic, Bedrock, Ollama, or Hugging Face.
• 2+ years of experience building agentic AI systems and workflows.
• 2+ years of experience developing AI and ML algorithms or technologies, such as LLM inference, similarity search, vector databases, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
• 2+ years of experience right-sizing models, instance counts, and hardware types to meet requirements such as context length and token inputs and outputs.
• 9+ years of coding experience with more than two of the following: Go, Java, JavaScript/TypeScript, Python, Rust, C#, or Scala.
• 5+ years of experience contributing to open-source frameworks.
• 5+ years of experience with frontend JavaScript or TypeScript frameworks.
• 5+ years of experience creating synchronous and asynchronous APIs.
• 4+ years of experience with databases and database management systems.
• 4+ years of experience with CI/CD pipelines, infrastructure as code, and automated testing frameworks.
• 4+ years of experience using Git-based version-control systems such as Git, GitHub, or Bitbucket.
• 4+ years of experience troubleshooting technical issues in cloud environments.
• 3+ years of experience mentoring senior engineers and driving professional development within technical teams.
• 2+ years of experience using observability to identify and optimize performance bottlenecks in distributed systems.
• 2+ years of experience leading architectural design reviews and influencing enterprise-wide technical standards and methodologies.
• 1+ year of experience establishing and enforcing coding standards and design patterns across teams.
• 1+ year of experience implementing observability and reliability practices at scale.
• Experience influencing technology strategy at the portfolio or business-unit level.
• Experience leading cross-functional engineering efforts or large-scale technical initiatives.

Responsibilities

• Lead a portfolio of technology projects and a team of developers building distributed microservices and full-stack systems to help meet regulatory needs.
• Architect performant, responsive web interfaces and real-time streaming AI chat and agent interfaces using modern frontend frameworks.
• Build resilient, high-throughput microservices and APIs, including support for Server-Sent Events and WebSockets for real-time AI responses.
• Integrate AI agent capabilities with enterprise systems, databases, third-party APIs, and legacy software using tool-calling and function-calling paradigms.
• Architect and integrate rule-based, retrieval-augmented, and generative AI systems into unified production pipelines.
• Stay current with technology trends, experiment with new technologies, participate in internal and external technology communities, and mentor engineers.
• Collaborate with digital product managers to deliver cloud-based solutions.
• Provide technical leadership across teams and shape system architecture and long-term technology direction.
• Drive end-to-end design and implementation of large-scale distributed or cloud-native systems with high reliability and performance requirements.
• Partner with architects and product leaders to define platform roadmaps and shared services strategy.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior