Software Engineer, Data Platforms
Status: Open
- Pay
- $200,000–$280,000
- Location
- Remote
- Employment type
- Full-time
- Openings
- 1
- Posted
- 2026-09-10
About this opportunity
Required skills
- Python
- Typescript
- Coding Agents
- React
- Outcome-driven Approach
What you'll do
- 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—often in parallel—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
- 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.
- 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.
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.