AI Software Engineer building AI-powered development tools in legal tech startup. Focused on enhancing automation and development workflows within specialized AI systems.
Responsibilities
Build and extend The Factory, our multi-agent system that processes GitLab issues end-to-end through specialised agents.
Ship production-grade workflows that move from issue → plan → code → review → merge request.
Iterate quickly while keeping quality high through strong interfaces, tests, and system design.
Design robust agentic workflows using tools like BAML, MCP, and DSPy (or equivalents).
Write the glue between LLMs and real codebases: implement context retrieval across repos: ownership boundaries, relevant files, conventions, and dependencies.
Build code generation and automated review loops that respect architecture and patterns in the codebase.
Stay AI-native and keep us ahead: work daily with AI-native dev tools: Claude Code, Codex, Gemini CLI, and decide what’s worth integrating (and what isn’t).
Requirements
You’ve actually built with AI coding/agent tools in real workflows (not just demoed them).
Strong TypeScript and/or Python (bonus if you’ve worked with Ruby on Rails).
Comfort with prompt design, agent orchestration patterns, and basic LLM evaluation (offline and/or in-product signals).
You understand software architecture well enough to teach an agent about it: boundaries, trade-offs, conventions, and what “good” looks like in a real codebase.
Hard requirement (the only one): hands-on experience with at least one AI-native dev/agent tool (e.g. Claude Code, Codex, Gemini CLI, or similar).
Benefits
Autonomy over how and when work is delivered
Access to necessary systems, tools, and documentation
Clear scope of work, with clear success criteria and meaningful deliverables
Opportunity to work on complex, high-impact problems
Exposure to enterprise / scale-up environments
Ability to shape systems, processes, or architecture
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