AI Infrastructure Engineer

AI Infrastructure Engineer WHO WE ARE Percepta's mission is to transform critical institutions with applied AI. We care that industries that power the world (healthcare, manufacturing, energy) benefit from frontier technology. We collaborate with industry-leading customers to drive AI transformation. We bring: - Forward-deployed expertise in engineering, product, and research - Mosaic, our in-house toolkit for rapidly deploying agentic architectures - Strategic partnerships with Anthropic, McKinsey, AWS, and the General Catalyst portfolio Our team is a fast-growing group of Applied AI Engineers, Embedded Product Managers, and Researchers motivated by getting frontier AI into the places that actually run the world. Percepta is a direct partnership with General Catalyst. ABOUT THE ROLE We're hiring an AI Infrastructure Engineer to own the infrastructure, deployment, and operational reliability that powers Percepta's AI systems, including the autonomous agents at the core of what we ship. Part of the work is hardening what exists: tightening our Terraform footprint, strengthening deployment pipelines, bringing more rigor to how we manage infrastructure across regions and providers. Part of it is building what's missing. And part of it is genuinely new territory, figuring out what SRE means when the systems you're operating make autonomous decisions. The infrastructure patterns for the agentic systems of the future don't exist yet. You'll help define them. WHY THIS IS DIFFERENT - You're deploying autonomous systems. The infrastructure contract changes when your workloads have agency. - Observability means understanding why an agent made a decision, not just whether a pod is healthy. - The gap between research and production is real here. Our teams move optimization algorithms and AI systems from research environments into production, and you'll be part of that handoff. MLOps experience isn't required, but you'll be closer to that boundary than most infra roles. - Small team. Real ownership. You're making foundational decisions, not inheriting someone else's. WHAT YOU'LL DO - Define infrastructure patterns for multi-agent systems that need to be observable, controllable, and recoverable in ways traditional apps don't require - Own and evolve our IaC stack: Terraform and Kubernetes across AWS, GCP, and Azure - Build observability primitives for agentic workflows, tracing agent decisions and execution paths, not just service latency and pod health - Design and maintain CI/CD pipelines that give teams fast, trustworthy feedback from commit to production - Build operational foundations: monitoring, alerting, incident response, and the new patterns that emerge when AI systems are participants in that response - Work across engineering teams to meet the reliability and compliance requirements of the institutions we serve (SOC 2, HIPAA, regulated environments in healthcare and energy) WHAT WE'RE LOOKING FOR - 5+ years building and operating production infrastructure in DevOps or SRE roles - The kind of engineer who sees a manual process and can't rest until it's automated well, not just scripted - Strong hands-on Terraform experience - Deep experience with at least 1 major cloud provider (AWS, GCP, or Azure): networking, IAM, cost management, the operational realities of production workloads - Solid Docker and Kubernetes experience in production. We run managed clusters across all 3 major clouds; this is a core part of the role - Experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, or similar) - Scripting proficiency in Python, Bash, or similar - High agency: you don't wait for a ticket to fix what's broken, but you communicate, collaborate, and bring the team along - Genuine curiosity about AI systems, not just the infrastructure running them. You want to understand what you're operating - You find it interesting (not alarming) that some systems you'll operate will be making ... (truncated, view full listing at source)