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# Agentic AI Developer

- **Company:** ASI Government, Inc.
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Build Automation, Microsoft Azure, Databases, Continuous Integration, Python (Programming Language), Regression Testing, OpenAI, Software Engineering, TypeScript, Data Logging, LangChain, ReactJS, Retrieval-Augmented Generation, Large Language Models, Software Application Programming, Llamaindex, Agentic-AI, Build Management, Containerization, AI Platforms, Kubernetes, Amazon Bedrock, CrewAI, Front End Software Development, Invoking Functions, Model Context Protocol, Agent SDK, Semantic Kernel, Software Version Control, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.thejobnetwork.com/job/c761fd70-982d-4a2e-aa5a-427721183427/agentic-ai-developer

## About the Role

* 5+ years of professional software development experience, including 2+ years building applications on large language models (tool use/function calling, retrieval-augmented generation, and multi-step agent workflows).
 * Strong Python skills and hands-on experience with at least one agent or LLM orchestration framework (e.g., LangGraph, LangChain, LlamaIndex, CrewAI, Semantic Kernel, or a model provider's agent SDK).
 * Experience evaluating LLM output: building test sets, measuring accuracy, and analyzing failure cases, including regression testing across model or prompt changes.
 * Experience writing software that other teams deploy, with version control, CI/CD practices, and clear technical documentation.
 * Experience with executive client engagement in the federal space, including pitch meetings, capability briefings, and live demonstrations for agency leadership.
 * Ability to obtain and maintain a Secret security clearance.

Preferred:

 * Experience building AI systems under federal or DoW security controls (e.g., Risk Management Framework, ATO processes, FedRAMP, NIST AI Risk Management Framework).
 * Experience in document-heavy domains such as contracts, procurement, invoices, or financial records; familiarity with DoW logistics or supply chain operations is a plus.
 * Experience deploying AI services in a government cloud environment (e.g., AWS GovCloud/Amazon Bedrock, Azure Government/Azure OpenAI).
 * Experience building MCP servers or similar standardized tool integrations for internal APIs, databases, or document stores.
 * Front-end experience (e.g., React/TypeScript) building review screens for people who check agent output.
 * Experience with containerization and orchestration (Docker, Kubernetes).

## Description

* Design and build agentic AI workflows: large language model (LLM) agents that use tools, retrieve from documents and data, and complete multi-step tasks with built-in human review points.
 * Build automation for client use cases such as contract modification automation, contract data dashboarding, and invoice reconciliation.
 * Connect agents to data sources, APIs, and interfaces in partnership with data scientists, full-stack developers, and cloud engineers, using standardized integration patterns such as Model Context Protocol (MCP) where appropriate.
 * Build evaluation into every agent, including test sets, accuracy measures, and logging, so behavior can be verified before and after release.
 * Design guardrails for responsible AI use: human approval steps, least-privilege permissions, and audit trails that hold up in a government security review.
 * Package each build for client deployment teams, with the documentation needed for deployment and Authority to Operate (ATO).
 * Participate in executive client meetings and pitch sessions with federal agency leadership: demonstrate agents, explain how they work and what they need to run, and answer technical questions.
 * Help shape demos and technical content for new business pursuits and capability briefings alongside practice leadership and business development.
 * Follow the practice's delivery methodology and work from priorities set by development leadership.