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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Agentic Systems Full-Stack Software Engineer, Senior - **Company:** Booz Allen Hamilton Inc. - **Location:** Fayetteville, NC, United States - **Experience:** Expert - **Salary:** $86,800.0 - $198,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Generation, Code Review, Databases, Relational Databases, Cursor, Programming Tools, Django Web Framework, Identity and Access Management, Issue Tracking Systems, Python (Programming Language), Open Source Technology, Software Engineering, Systems Integration, TypeScript, Web Application Frameworks, Data Processing, ReactJS, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Claude Code, Kubernetes Helm Charts, Caching, Agentic-AI, Gitlab, Git, Fastapi, Vue.js, SC Clearance, Database Migration, Kubernetes, Invoking Functions, Model Inference, Terraform, Dynatrace, Docker, Microservices - **Published:** November 6, 2026 - **Apply:** https://www.juju.com/job/7_BA9504B5D5034FAA703EA84C64F94495 ## About the Role merge requests, code review, and CI/CD pipelines such as GitLab or GitHubSecret clearanceHS diploma or GED and 2+ years of experience with agentic AI full-stack development, or Bachelor's degreeAbility to obtain a DoD 8570 IAT Level II Certification within 60 days of hire dateNice If You Have: Experience managing and deploying applications in an air-gapped environmentExperience with attribute or policy-based authorization systems, including AWS IAM, Cedar, OPA, Rego, or CasbinExperience with data handling in classified environments, including classification markings, compartments, or clearance-based access controlExperience with GPU workload scheduling on Kubernetes, including time-slicing, MIG, or device plugins, OpenTelemetry, and distributed tracing across a microservice fleetExperience building evaluations, benchmarks, or regression harnesses for LLM-backed featuresExperience creating and conducting automated unit and system integration tests to identify and provide feedback on failed modules and componentsExperience contributing to open-source developer tooling, agent frameworks, or MCP serversPossession of excellent verbal and written communication skills to communicate technical ideas and deliver briefings with cross-functional teamsMaster's degreeSecurity+ CertificationClearance:Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information;Secret clearance is required.CompensationAt Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. ## Description Agentic Systems Full-Stack Software Engineer, SeniorThe Opportunity: Most engineering roles ask you to write software. This one asks you to design it, direct it, and stand behind it. As a full-stack software engineer, you can take a problem from vision to production-ready in a fast, agile environment. If you're looking for the chance to not just develop software, but to help design and create systems that make a difference, we need you on our team.You'll work in an agentic-first codebase, where a large share of the code is drafted by AI agents working from a specification you write, then reviewed, tested, and shipped by you. The job is less about typing and more about judgment, decomposing work into verifiable pieces, writing the spec and the tests that constrain the agent, and reviewing what comes back with the same rigor you'd apply to a teammate's work. Engineers who can only prompt struggle here. So do engineers who insist on handwriting everything. We're looking for the one who does both well, and who can tell the difference between output that looks right and output that is right.You'll help clients overcome their most difficult challenges using the latest architectural approaches, tools, and technologies. You'll make sure the solutions your team delivers account for the current architecture and operating environment as well as future functionality and enhancements. And you'll help define how software actually gets built over the next five years, rather than just adopting someone else's workflow.What You'll Work On:Ship features end-to-end across ten Python and FastAPI microservices and a React or TypeScript front end including database migration, service logic, API contract, UI, and tests in a single change.Author and maintain the agent harness that makes this codebase productive for AI agents including project-level instructions, reusable skills, specialized subagents, and the evaluations that tell you when the harness has regressed.Extend a multi-tenant authorization system modeled on AWS IAM including policy evaluation order, organizational guardrails, cross-organization consent, per-service database isolation, and audit trails that hold up under inspection.Deploy and operate LLM inference on Kubernetes including vLLM on GPU nodes, Helm charts, model routing, and per-request usage and cost accounting.Own infrastructure as code including Terraform modules for databases, caches, object storage, queues, and secrets across multiple environments.Promote releases through a staging production air-gapped enclave ladder, including packaging for environments with no internet egress.Review AI-generated changes for correctness, security, and architectural fit and when a class of mistake recurs, fix it in the harness rather than in the diff.Join us. The world can't wait.You Have: Experience with full-stack development, including a Python web framework such as FastAPI, Flask, or Django and a modern JavaScript framework such as React, Vue, or SvelteExperience with cloud computing, including AWS, GCP, or AzureExperience with relational databases, including schema design, query performance, versioned migrations, and KubernetesExperience with agentic engineering using tools such as Claude Code, Codex, Cursor, Docker, or Helm, including writing project-level agent instructions, decomposing work into agent-executable specifications, and reviewing AI-generated code before mergeExperience with infrastructure as code, including Terraform, and managing and deploying LLMs in a Kubernetes environmentExperience with LLM application patterns, including retrieval-augmented generation, vector databases, tool or function calling, or streaming inferenceExperience with Agile development and Git-based collaboration workflows, including issue tracking