> Markdown version of [/jobs/ext/4588286-principal-software-engineer](https://www.wearedevelopers.com/jobs/ext/4588286-principal-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer - **Company:** Roblox - **Location:** San Mateo, CA, United States - **Experience:** Expert - **Salary:** $345,040.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Large Language Models, Backend, Agentic-AI, Information Technology, Machine Learning Operations - **Published:** November 5, 2026 - **Apply:** https://careers.roblox.com/jobs/8221568?gh_jid=8221568 ## About the Role * 8+ years of experience building and operating large-scale distributed systems, including technical leadership across multiple teams. * Deep experience designing backend platforms used by other engineering teams. * Hands-on experience with production AI/ML systems, such as model serving, orchestration, LLM integration, or agentic execution loops (planning, tool use, recovery, long-running workflows). * A strong understanding of tool and skill design and structured evaluation for AI systems. * The judgment to weigh tradeoffs and make pragmatic calls under ambiguity. * A BS in Computer Science or a related field, or equivalent professional experience. ## Description * Excited to define how AI agents create at scale, and to stay hands-on while doing it. * A clear communicator who can explain complex technical direction to engineers, product, and leadership. * Experienced with workflow engines (e.g., Temporal), multi-provider model routing, or AI cost management (bonus). You Will: * Own the technical architecture and long-term roadmap for the Build agent platform. * Design for reliability, safety, observability, and cost efficiency in production AI workloads, including usage metering and model-routing strategy. * Define how we measure agent quality and build the evaluation infrastructure that drives model, prompt, and skill decisions. * Partner with Build product teams, ML infrastructure, and Safety to ship new capabilities quickly and safely. * Raise the engineering bar through design reviews, mentorship, and hands-on technical leadership.