[Hiring] MLOps Engineer @AHL - Saaf AI

Role Description

We’re hiring an MLOps Engineer to own the infrastructure our AI runs on. Our AI systems are already in production and already touching real loans. The next chapter is making them scale, deploy safely, and change quickly:

• Infrastructure that absorbs real production load.
• A promotion path that makes shipping boring.
• Internal tooling that lets the team improve AI behaviour without an infrastructure engineer in the loop for every change.

This is not a role where you inherit a mature platform and keep the lights on. You’ll take AI services that were built to prove the idea and turn them into systems that hold up under load, deploy predictably across environments, and give the rest of engineering a safe, fast path to production.

This role is right for you if:

• You’ve taken AI or ML systems from a single deployment to infrastructure that scales — and you’ve been on call for the result.
• You treat infrastructure as a product with users, not a ticket queue.
• You think deploys should be boring, reversible, and frequent — and you’ve built the systems that make that true.
• You’d rather remove yourself from the critical path than be the person everyone has to ask.

Qualifications

• Production infrastructure ownership: You’ve deployed and operated containerized services in production under real traffic.
• Infrastructure as code: You build environments declaratively and reproducibly.
• CI/CD depth: You’ve built pipelines that others depend on daily.
• Strong Python: You should be able to read and change application code, profile it, and fix it.
• Operational judgment: You can debug a production problem across application, network, and infrastructure boundaries.
• Ownership without guardrails: You drive work end to end — design, implementation, deployment, monitoring, and follow-up.
• Fast iteration: You ship incrementally and improve.

Requirements

• Experience operating LLM or ML workloads in production.
• Cloud deployment experience (AWS preferred).
• Experience in fintech, lending, insurance, or another regulated industry.
• Built internal developer platforms or self-serve tooling that non-infrastructure engineers actually used.
• Full-stack comfort — you can build a lightweight UI or internal tool when the platform needs one.

Benefits

• Competitive compensation.
• Unlimited PTO.
• Remote-first with flexible hours.
• $2,000/year professional development budget.
• Home office setup stipend.