AIOps Lead

Perhire.ai

Bengaluru • Not disclosed

4 hours ago

On-Premises

About the job

An AI system that's up but wrong is worse than one that's down. Most engineering teams don't have the mandate to care about that distinction. Most senior engineers do, and never get the role that lets them act on it. This one does. Through Away Talent Pods, a TaaS model by Perhire x away.center, we're matching a pre-vetted AIOps Lead to a partner company building production AI infrastructure in Bangalore. Full-time, on-premises. You'll work for one company, embedded in their culture and tools from day one. Same ownership as an in-house hire. None of the project-to-project churn. What we're looking for • Shipped LLM or AI system logic to production. Not Kaggle, not a chatbot, not a side project. Live systems, real users, consequences that mattered. • Deep experience designing event-driven systems where out-of-order, delayed, and duplicate events are first-class concerns, not edge cases you document and ignore. • PostgreSQL strength: version-aware schemas, idempotency from first principles, safe state transitions at the data layer. • Failure-first instincts. DLQs, backoff, circuit breakers, and graceful degradation show up in your designs without prompting. • 4–5 years across Backend, SRE, DevOps, or Platform Engineering with meaningful time spent on production AI systems. How we hire → Resume and portfolio review→ Technical interview, 30 minutes→ Assignment→ Onboarding Why this model is different ✅ Pre-scoped role brief. The mandate is defined, the expectations are clear, and scope creep is not the first week's problem. ✅ AI-matched to your profile. Perhire's platform evaluates fit before the process starts, so the conversation has context from day one. ✅ away.center workspace in Koramangala, Bangalore. Acoustically treated, designed for deep work, built for the kind of engineer this role needs. ✅ Full employer infrastructure: compliance, contracts, payroll, and IP protection, handled from day one. Bangalore | On-Premises | Full-Time If you've spent years watching AI systems fail in ways nobody noticed, and felt the pull to fix it before it cost someone, apply now.