Fullstack Software Engineer

About the Role

This is an AI-native fullstack engineering role building human data platforms. You will own features end-to-end, from backend services and data pipelines to the frontends experts use daily. The role sits between traditional fullstack and research engineering. Coding agents are your primary development workflow, and you will work closely with research engineers, operations, and product to turn requirements into reliable production systems.

Key Responsibilities

• Design and ship fullstack features across backend APIs, data pipelines, and React frontends.
• Own client-facing data delivery and platform infrastructure, including exports, access control, and reliability.
• Scope work around outcomes, direct coding agents, review changes at the architecture level, and iterate until shipped.
• Build and maintain services in Python (FastAPI) and TypeScript.
• Contribute to data modeling, schema design, and query performance across relational and document databases.
• Partner with research engineering, operations, and product to translate platform needs into production-ready systems.
• Improve the frameworks, checks, and evals that make agent-driven development faster without sacrificing quality.
• Troubleshoot production issues and build resilient, observable systems.

Requirements & Tech Stack

• Strong fundamentals in Python and TypeScript, with experience building CRUD applications using frameworks such as FastAPI/Flask and React.
• Working knowledge of databases such as PostgreSQL, MongoDB, or SQLite and core data modeling principles.
• Experience deploying services on a major cloud platform (GCP, AWS, or Azure).
• Coding agents such as Claude Code, Cursor, or Codex are your default development workflow, and you can clearly explain how you use them.
• Ability to turn outcomes into plans, direct agents, verify results, and identify architectural issues agents may miss.
• Understanding of agent loops, MCP, tool/data integrations, permissions, and security.
• Familiarity with context management, RAG, and evals for testing agent workflows.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field, or equivalent practical experience.
• 0–5 years of software engineering experience, or strong shipped projects as a recent graduate.

Preferred Qualifications

• Exposure to RL concepts or environments, including tasks, actions, and rewards.
• Experience with coding data pipelines or task-authoring platforms.
• Familiarity with CI/CD, deployment pipelines, and DevOps fundamentals.
• Experience contributing to team projects, open-source software, or startups.