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Jobs(30,538)/Staff Engineer Role(812)/flox (3) - Member of Technical Staff - AI Product Engineer
flox

flox - Member of Technical Staff - AI Product Engineer

United States$150k - $250k3w ago
RemoteStaffNALogisticsStaff EngineerTech LeadRustPythonTypeScriptClaudeCursor

Requirements

• 5+ years of professional software engineering experience building and shipping production systems • Production experience with Rust, Python, and/or TypeScript—strong in at least one, comfortable across the others • Daily use of agentic coding tools (Claude Code, Cursor, Copilot, or similar) as a primary development workflow • Experience building AI development infrastructure beyond personal use: harnesses, agent skills, automation scripts, evaluation frameworks, or workflows that a team adopted • Strong engineering fundamentals—architecture judgment, ability to reason about complex codebases, discipline to maintain quality when code generation is fast and cheap • Clear communication skills and the ability to document workflows and practices in ways other engineers actually use • Developer tooling, CLI, or infrastructure engineering background • Familiarity with Nix, NixOS, or reproducible build systems • Tech lead experience: owning delivery, planning work, leading a team through execution • Background in software supply chain tooling, package management, or build systems • Contributions to open-source AI development tooling, skills, or harness frameworks

Responsibilities

• Design, build, and ship features for the Flox platform—working primarily in Rust, Python, and TypeScript across CLI tools, backend services, and infrastructure • Own the quality and reliability of what you ship: write tests, review code, make architectural decisions that balance speed with long-term system health • Write production code using agentic coding tools as your default workflow, focusing on the most complex and ambiguous parts of the system • Build and maintain AI development infrastructure for the team: harnesses, context engineering (CLAUDE.md http://CLAUDE.md, skills, rules files), automated feedback loops, and evaluation frameworks • Evaluate new agentic development tools and practices as the landscape evolves—run experiments, measure results, and make evidence-based recommendations on what to adopt • Help engineers across the team develop sophisticated, reliable AI-assisted workflows—document what works, build shared practices, and codify lessons so they compound • Exercise judgment on when AI agents accelerate real work and when they introduce risk, complexity, or false confidence

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