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.
ResponsibilitiesIdentify 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
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
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)
Skills Required
- 3+ years of software engineering experience
- Hands-on experience with LLM-based coding tools
- Strong understanding of software development workflows
What We Do
FuriosaAI designs and develops data center accelerators for the most advanced AI models and applications. Our mission is to make AI computing sustainable so everyone on Earth has access to powerful AI. Our Background Three misfit engineers with each from HW, SW and algorithm fields who had previously worked for AMD, Qualcomm and Samsung got together and founded FuriosaAI in 2017 to build the world’s best AI chips. The company has raised more than $100 million, with investments from DSC Investment, Korea Development Bank, and Naver, the largest internet provider in Korea. We have partnered on our first two products with a wide range of industry leaders including TSMC, ASUS, SK Hynix, GUC, and Samsung. FuriosaAI now has over 140 employees across Seoul, Silicon Valley, and Europe. Our Approach We are building full stack solutions to offer the most optimal combination of programmability, efficiency, and ease of use. We achieve this through a “first principles” approach to engineering: We start with the core problem, which is how to accelerate.
