Full Stack Python Engineer

The Health and Services Operation of Leidos is seeking a Full Stack Python Engineer to support a Critical Health program

Candidates MUST:
Be US Citizen or Green Card holders with the ability to obtain a level 5 Public Trust Clearance

AND

Be currently located in the UNITED STATES for the current three consecutive years.

Role is a telecommuting role.

The GRACE team builds and operates the agency's purpose-built AI assistant — a production system used daily by all ARPA-H staff to accelerate healthcare research, program launches, and agency operations. GRACE is a Python-first, full-stack platform built on Chainlit, integrating OpenAI GPT, Anthropic Claude, and Google Gemini models with real-time streaming interfaces, custom Mermaid diagram rendering, GeoJSON map generation, Slack channel search, SharePoint document indexing, and external API connections, all running on Azure in a FedRAMP-aligned environment.

We are hiring a Full Stack Software Development Engineer to backfill a critical seat. You will work on the full vertical: Chainlit application layer, custom component development, Python backend services, API integrations, and production operations.

This is not a role where front-end and backend are handed off between people. You own both. You ship both.

We ship on a weekly cadence. We hold a <4-hour SLA for issue response. The bar is high and the mission is real. We operate with a product-led, customer-obsessed culture and a bias for shipping over planning.

Key Job Responsibilities

Full Stack Application Development (Chainlit + Python Backend)

• Own the GRACE application layer end-to-end — Chainlit lifecycle hooks, chat profiles, session management, streaming configuration, data persistence, and human feedback integration
• Build and extend custom Chainlit components in React/TypeScript for advanced rendering surfaces: Mermaid v11 diagrams, GeoJSON/OpenStreetMaps, Imagen4 image outputs, and multi-model conversation state
• Design, build, and maintain Python backend services and API integrations powering GRACE's tool-calling architecture: internal document search (SharePoint/vector search), Dimensions API (, Google Search, Slack channel history, and Imagen4 image generation
• Own the Entra ID OAuth 2.0/OIDC authentication integration within Chainlit, ensuring seamless and secure SSO flows
• Design and maintain secure file handling pipelines all type types — validation, sanitization, storage, and retrieval
• Build and maintain multi-LLM routing logic across OpenAI GPT, Anthropic Claude, and Google Gemini — including model switching, streaming completions, tool-call orchestration, and fallback handling

Customization & Front-End Extension

• Extend Chainlit's front-end via CSS/JS customization, 
• Write custom React components where Chainlit's native rendering falls short — Mermaid v11 is a live example of this; you will own and evolve it
• Ensure all rendering surfaces meet accessibility standards

Collaboration & Customer Obsession

• Work directly with the GRACE product team and ARPA-H stakeholders to translate user feedback into shipped improvements on a weekly cadence
• Lead code reviews, set engineering standards, and mentor teammates
• Contribute to architecture decisions, technical documentation, and internal engineering wikis

Basic Qualifications

• Bachelor's degree in computer science or data science
• 7+ years of non-internship professional software development experience
• 7+ years of Python as a primary programming language in production environments
• 7+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience building and shipping production LLM/AI chat applications — streaming, tool-calling, multi-turn conversation state management
• Experience with Chainlit or a comparable Python-first conversational AI framework (Streamlit, Gradio, or equivalent) in a production context
• Experience building and owning REST APIs and backend service integrations end-to-end
• Experience with OAuth 2.0 / OIDC authentication flows in production systems
• Experience with cloud infrastructure (Azure preferred) and containerization (Docker)
• Experience with modern JavaScript/TypeScript tooling and frameworks
• Experience working with relational databases (eg PostgreSQL), including schema design and writing efficient queries.
• Experience as a mentor, tech lead, or leading an engineering team

Preferred Qualifications

• 7+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Chainlit-specific experience: custom component development, 
• Experience writing custom React/TypeScript components and managing application state (eg Recoil, Redux, or similar)
• Experience with a modern UI frameworks and styling approaches (MUI, Tailwind, or similar)
• Experience with multi-LLM API integration (OpenAI, Anthropic Claude, Google Gemini) including streaming completions and tool-call orchestration
• Experience with vector databases and semantic search pipelines (Azure AI Search, pgvector, Pinecone, or equivalent)
• Experience in FedRAMP, FISMA, or NIST 800-53 compliant Azure environments
• Experience with CI/CD pipelines (GitHub Actions or equivalent) and production observability tooling
• Experience at a high-velocity startup or product-led organization with weekly ship cadences

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.