Principal Platform Engineer - AI Ops, Backend, Reliability & Security

IR Labs is the innovation lab inside Integrated Research where small, cross-functional squads chase outsized, industry-defining opportunities. We operate like a funded startup-rapid sprints, bold experimentation, zero bureaucracy-backed by the global footprint and resources of a public company. Our charter is simple: turn cutting-edge AI research into products that customers can’t imagine working without. We target the hardest problems in software and then move fast to ship solutions that create 10x impact.

Our flagship is Agentic SQA - a software quality system that turns noisy signals (static analysis, fuzzers, sanitizers, CI output) into context-aware triage, validated actions, and developer-ready outputs. We’re in beta now, starting narrow on a focused C/C++ risk-analysis workflow targeting a specific bug class, and expanding from there into broader coverage, richer evidence, and stronger control layers. The stack combines LLVM/clang static analysis, a code knowledge graph, and agentic LLM workflows. The direction is bigger than code review: a systems verification platform that closes the gap where human-speed review is breaking down.

If you thrive on autonomy, crave world-class technical challenges, and want to see your ideas hit production quickly, IR Labs is your launch pad. Join us and help build the future, one breakthrough at a time.

Before you apply: Agentic SQA is live and free to use. Install and run it. Form a view. We’ll discuss that during the interviews.

Who We’re Looking For:

The founding Principal Platform Engineer will join a lean team and work closely with senior technical leaders to accelerate execution and deliver high-impact infrastructure to allow AI teams to focus on innovation. If you want to own the core platform that turns AI systems into a reliable, secure, and scalable product and build the backend services that power onboarding and operations, create streamlined “paved roads” for engineering, and productionize AI workloads with strong MLOps foundations, this role was written for you.

What You’ll Do:

• Own the product platform, not just the infrastructure: build the core platform layer that turns our AI systems into a reliable, supportable product customers can onboard to and use daily.
• Ship critical backend systems: design and implement core services/APIs that power signup/sign-in, tenancy, permissions, billing/entitlements, provisioning, and internal workflows so customer onboarding is seamless and repeatable.
• Build “paved roads” that prevent engineering drag: create a standardized, self-serve path from feature → deploy → operate so teams can ship without repeated bespoke work, manual steps, or fragile runbooks.
• Keep the AI critical path clean: absorb platform/ops/MLOps work that would otherwise pull our AI Scientist/MLE into toil and customer support, protecting our highest-leverage innovation hours.
• Productionize AI workloads: build pragmatic MLOps and GPU operations foundations (serving/training workflows, model artifact distribution, utilization-aware scheduling, caching/cold-start strategies) so AI cost and latency remain controlled as we scale.
• Create reliability as a system property: define SLIs/SLOs and error budgets, then enforce them through release standards, testing discipline, rollout patterns, and incident practices.
• Embed security into the platform primitives: implement safe-by-default patterns for identity, access boundaries, secrets, and dependency hygiene so security is “how the platform works,” not a separate checklist.
• Design for resilience with cost discipline: architect multi-region strategies (backup/restore, DR, failover) that are as simple as possible while meeting availability goals.
• Make observability actionable: build high-signal metrics/logs/traces and operational dashboards that reduce noise and accelerate diagnosis; run blameless incident reviews that permanently reduce repeat failures.
• Be a force multiplier across a senior team: partner closely with data infra, compiler, and AI leadership - review designs, unblock execution, and ship high-impact work directly when needed.