About the Role

The Compiler team at FuriosaAI builds the software stack that enables ML models to run at peak performance on our AI accelerator hardware. This is a newly established role — there's no playbook yet. You'll be the first person to define and operationalize AI-assisted engineering workflows for the team: identifying high-leverage bottlenecks, running experiments, and shipping repeatable tooling + playbooks that stick. While you’ll be embedded in the Compiler team, compiler specialization is not required — your scope can span development, code review, debugging, CI/testing, documentation, and project execution.

If you're the kind of engineer who gets uncomfortable without a clear job description — this role isn't for you. If you're the kind who sees an undefined space and immediately starts mapping it — read on.

Responsibilities

• Identify pain points and leverage opportunities across the engineering workflow (development, code review, debugging, CI/testing, documentation, and project execution)

• Research, prototype, and benchmark AI/automation tools (e.g., coding agents, LLM-assisted review, debugging assistants) against real team workflows

• Design and maintain team-specific prompt libraries, workflow templates, and integration guides (IDE, code review, CI, debugging, documentation)

• Improve CI/testing signal quality and feedback loops (e.g., flaky test reduction, failure triage workflows)

• Lead onboarding sessions, regular Q&A sessions, and internal knowledge sharing for newly adopted tools

• Define and track adoption + impact metrics (e.g., PR cycle time, review turnaround, time-to-triage regressions, CI flakiness), and iterate based on data and feedback

• Monitor the AI tooling ecosystem and surface relevant developments to the team

Minimum Qualifications

• 3+ years of software engineering experience

• Hands-on experience with LLM-based coding tools (e.g., GitHub Copilot, Cursor, Claude Code, Codex, or equivalent)

• Strong understanding of software development workflows from the perspective of a practicing engineer

• Ability to rapidly evaluate new tools and translate findings into actionable team guidance

Preferred Qualifications

• Background in compiler engineering, systems programming, or static analysis

• Experience building or customizing LLM-based agents or tooling via API

• Track record of driving internal tooling adoption or developer experience improvements

• Experience producing technical documentation, runbooks, or internal tech talks

• Experience improving engineering workflows (DevOps, CI/CD, developer productivity, or technical program execution)

Contact

• recruit@furiosa.ai