Lead Software Engineer, AI-Native

New

FreeWillNonprofit technology

United States (Excluding AL, CO, LA)Full-TimeLead

Salary$190,000 to $210,000 (plus equity and benefits)

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Job Details

Have 7+ years of experience as a software engineer.
Have strong experience building and shipping full-stack production systems.
Have experience cultivating mentorship and knowledge sharing across engineering teams, particularly around AI-native system orchestration.
Have experience building development tooling and workflows that incorporate quality from the start.
Demonstrate experience using agentic coding tools such as Cursor, Copilot, Codex, or Claude Code in real development workflows.
Be familiar with LLM behavior, evaluation, and prompt iteration techniques, including chain-of-thought, few-shot examples, and agentic loops.
Be able to write clear technical specifications and break problems into structured, verifiable units of work.
Have experience with modern web stacks such as React, Node.js, TypeScript, APIs, and cloud infrastructure.
Be able to ship quickly while maintaining quality in ambiguous, fast-moving environments.
Have strong debugging and systems thinking skills to validate and improve AI-generated outputs for correctness, security, and performance.
Be comfortable working autonomously with minimal process on small teams while maintaining rigor.
Have strong written communication skills for specifications, prompts, and documentation.

Lead AI-native software development workflows using tools like Claude Code, Codex, and Cursor to generate, iterate on, and ship production code.
Mentor engineers across R&D on AI-native development practices and share patterns others can adopt.
Translate product requirements into technical specifications, prompts, and system instructions for AI-driven development.
Own end-to-end delivery from specifications through AI-written implementation, automated validation, and production rollout.
Build repeatable harness engineering practices for developing AI-generated code.
Partner with a small pod to rebuild and improve existing product flows.
Design robust, testable, and maintainable systems to manage code comprehension and technical debt.
Refine and document workflows for spec-driven development, agentic engineering, and AI-driven QA.

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