Full Stack Agentic Developer
Chicago, IL, United StatesAll locationsChicago, IL, United StatesBoston, MA, United StatesDallas, Texas, United StatesHouston, Texas, United StatesNew York, NY, United StatesOakland, CA, United StatesWashington, DC, United States On-site
$150,000–$230,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
Charles River Associates is seeking a Full Stack Agentic Developer to help build and evolve a web-based AI platform that enables experts to translate domain expertise into scalable, validated AI-driven workflows. This is a senior full stack engineering role for someone who began with strong product and platform skills and has advanced into LLM-powered agentic systems. The Full Stack Agentic Developer will own the path from user intent to agent action to reviewed output. This person will build the product workflows and underlying agentic capabilities that let consultants and domain experts create sessions, upload and organize materials, launch AI-assisted work, monitor agent activity in real time, review files and intermediate outputs, and rely on the platform for high-quality analytical work in confidential, high-stakes environments.
What you'll bring
- Bachelor's degree in Software Engineering, Engineering, or other relevant discipline with programming/technology experience, advanced degree desirable;
- 6+ years of professional software engineering experience, with strong hands-on ownership across frontend, backend, and production product systems;
- Strong TypeScript skills across the stack, including modern React development and Node.js/Express API development;
- Experience building component-driven React applications with complex state, multiple interconnected views, real-time updates, and user-facing workflows that require careful error handling;
- Experience building or consuming real-time interfaces using server-sent events, WebSockets, streaming APIs, or similar event-driven patterns;
- Experience with LLM tool calling or function calling, including tool schema design, streaming tool input/output, multi-turn execution, and provider-specific implementation details;
- Strong prompt engineering ability for structured, multi-step workflows, including prompts that encode policies, methodology, roles, and tool usage expectations;
- Comfort working in Python for agent tools, data processing, automation, evaluation, and integration with analytical libraries;
- Good understanding of browser authentication flows, JWT lifecycle, token refresh, CORS, secure cookies, role-based access, and frontend/backend security boundaries;
- Familiarity with PostgreSQL and API-driven application design, including practical awareness of schema design, queries, migrations, and data access patterns;
- Experience with Docker or Linux-based execution environments and practical understanding of isolation, filesystem access, dependency management, and runtime troubleshooting;
- Strong product judgment, debugging instincts, documentation discipline, and ability to reason about AI behavior, software behavior, and user impact at the same time.