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Ricursive Intelligence is a frontier AI lab building self-improving systems, starting with chip design. The company is reinventing chip development by closing the loop between AI and the hardware that fuels it, recursively accelerating progress toward artificial superintelligence. Backed by $335M from Sequoia, Lightspeed, DST, and NVIDIA Ventures, the team includes IMO, IPHO, and IOAA gold medalists, chip design pioneers (AlphaChip, ePlace, RL-CCD, INSTA, C3PO), chip leads from Apple Silicon and Google (TPU, OpenTitan), and top researchers from Anthropic, Google DeepMind, Stanford, and MIT.
Ricursive's research runs on infrastructure that must keep pace with the research itself: ML training and evaluation workloads, EDA tool flows, and a fast-growing team needing everything from cloud environments to developer workflows. This role owns that foundation—the pipelines, platforms, and systems that let a small team move like a much larger one.
You will own the infrastructure-as-code (IaC), continuous integration & deployment (CI/CD), and cloud platform end-to-end that keeps the lab running day to day. You will also collaborate closely with the team to build out the right observability stack for their needs while working around environment security limitations.
Key responsibilities:
• Design, build out, and extend the self-managed cloud platform with Terraform, setting the IaC patterns the rest of the team builds on.
• Own platform deployments spanning various environments, including performance, security, reliability, scalability, and adapting to evolving business requirements.
• Design, implement, and operate CI/CD pipelines in GitHub Actions for mission-critical repositories, working within strict security and deployment restrictions.
• Architect scalable AI tooling and developer experience workflows across multiple distinct user environments, working closely with physical design engineers.
• Build out the observability stack, covering pipeline health, application-level metrics, and ML workloads.
REQUIREMENTS:
• BS in CS, CE, EE, or closely related technical field, or equivalent practical experience.
• 4+ years of hands-on infrastructure/platform engineering, with ownership of systems others depend on.
• Owned production IaC architecture including maintenance and new features, not just consumed modules.
• Designed and implemented production CI/CD pipelines that build and ship reproducible artifacts, with attention to performance, scalability, and security.
• Prior experience with observability tooling for monitoring pipeline health and application-level metrics.
PREFERRED:
• Hands-on experience with GCP, Kubernetes, and GitHub Actions, including custom runner setups.
• Experience running ML infrastructure for training and evaluation workloads, including GPU/TPU compute.
• Familiarity with LLM observability tooling: tracing, evaluations, and cost & latency monitoring.
• Security depth: dependency supply-chain hardening, OIDC-based auth, least-privilege secrets, and compliance work such as SOC 2 or penetration testing.
• Early-stage startup experience: built infrastructure from zero or near-zero.
