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Role Description

We’re looking for a full stack developer to help build and extend LIGER, an enterprise AI platform that connects knowledge, systems, and agentic workflows to accelerate outcomes across federal missions. You’ll join a small, cross-functional team shipping a ground-up product redesign – and increasingly, building the agentic capabilities that make LIGER genuinely powerful.

This isn’t a maintain-the-backlog role. You’ll work across the stack, own features end-to-end, and help shape how AI agents are integrated into workflows that real users depend on. If you’re excited about building systems where models do real work – not just generate text – keep reading.

Responsibilities

• Build and ship full stack features across frontend (Angular, Typescript), backend (Node/Python), and the integration layer between them
• Design and implement agentic workflows: tool-calling, multi-step reasoning pipelines, and the infrastructure that makes them reliable
• Use AI coding tools as a daily part of your development workflow
• Integrate and maintain connections to external services, data sources, and APIs as part of agent execution flows
• Collaborate directly with our designer and engineering lead in working sessions – you’ll shape UX decisions, not just implement them
• Contribute to backend architecture decisions around agent orchestration, state management, and LLM interaction patterns
• Ship incrementally and stay close to users – we care about getting things in front of people, not perfecting in isolation

Qualifications

• 3+ years of full stack development experience, or fewer years with demonstrable depth in agentic or LLM-native development – comfortable owning both frontend and backend
• Experience using PostgreSQL to store, retrieve, and manage structured application data, with experience in database design, SQL development, and operational support
• Proficiency in Angular and TypeScript on the frontend
• Solid backend experience in Node.js and/or Python
• Hands-on experience building with LLMs (prompt engineering, API integration, tool use, and managing model outputs in production)
• Active use of AI-assisted development tools in your day-to-day coding workflow
• Experience designing and developing RESTful APIs and backend services that support scalable, maintainable integration across distributed application components
• Familiarity with agentic patterns: orchestration, tool-calling, retrieval-augmented generation (RAG), or multi-step agent flows
• Ability to move fast and iterate without heavy specs or detailed tickets

What Will Set You Apart

• A portfolio of side projects, personal websites, open-source contributions, or other evidence of a builder’s disposition – we care more about what you’ve built than where you’ve worked
• Demonstrated fluency with AI coding tools and a workflow that treats them as force multipliers, not novelties
• Experience with Model Context Protocol (MCP) – building servers, defining tools, or integrating MCP into an agent stack
• Experience building scalable document processing pipelines supporting text extraction, chunking, metadata enrichment, indexing, and persistence for downstream semantic retrieval use cases.
• Background working on AI-native products or internal tooling where models are core to the user experience, not bolted on
• Familiarity with frameworks like LangChain, LlamaIndex, or similar orchestration tools
• Experience developing software in environments governed by federal security and compliance requirements, with attention to secure coding practices, access control, auditability, and deployment constraints

Salary Information

Target salary range: $100,000 - 175,000. The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.