About InfrasAI

InfrasAI (formerly iLife Technologies) is a high-growth fintech and insurtech startup backed by top VCs, the same investors behind Uber, Netflix, Slack, and Ring.

InfrasAI helps financial services and insurance companies use AI Agents to build and QA complex workflow mappings at the speed of thought, with a streamlined human-in-the-loop process to ensure enterprise-grade accuracy and compliance.

About the Role

InfrasAI's platform, GitOps-driven Kubernetes across multiple AWS accounts and tenants, has so far been designed and operated by a single engineer who also serves as our AWS Solutions Architect and owns security across the platform. We're hiring the second.

This is not a junior backfill or a ticket-taker role. This person will be a true peer on platform, infrastructure, architecture, and security, owning major workstreams end to end and helping set technical direction. We're a small team, so this comes with real autonomy and real impact. The right person can take an ambiguous problem and own it without a playbook handed to them.

Quality of the hire is our number one priority. We would rather wait for the right person than fill the seat with the wrong one.

What You'll Own

• GitOps deployment architecture (ArgoCD, Argo Workflows, Helm) for a multi-tenant product — codifying it, hardening it, and evolving it as we grow.
• Observability and alerting: turning this into something we genuinely trust, where alerts mean something and we hear about problems before customers do. (Grafana, Prometheus, Loki.)
• Reliability and resilience: backups, disaster recovery, high availability, and the durability work that keeps us standing when something fails.
• Solution and systems architecture: shared ownership of how our systems are designed across the stack, not just how they run.
• Security — a security-first eye across the platform, covering infrastructure hardening, secrets management, least-privilege access, and keeping our systems and tenants safe.

What We're Looking For

• Strong solution and systems architecture depth. You can design whole systems and reason about tradeoffs across the entire stack, not just operate individual components.
• Deep AWS expertise at a solutions-architect level, ideally across multiple accounts.
• Strong security experience and a natural eye for it. You think about attack surface, least privilege, secrets handling, and tenant isolation by default, not as an afterthought.
• Deep, hands-on experience running production Kubernetes (EKS a plus) and infrastructure as code (Terraform).
• You've owned a production platform, not just contributed to one. You've been the person on the hook when it broke.
• Real CI/CD, GitOps, and observability experience.
• Hands-on experience building and leveraging AI systems into real production systems. You've started working AI into real systems, not just experimenting on the side. As an AI company in a fast-moving space, this matters to us.
• You think in failure modes. You design for the bad day, not just the happy path.
• You can operate independently, make good calls under ambiguity, and own the outcome.
• You make the people around you sharper, and you collaborate openly to pressure-test ideas and arrive at the most robust solution rather than the first one. Someone worth thinking out loud with.

Nice to Have

• Production experience with Go, Python, Java, Typescript.
• Multi-tenant SaaS infrastructure experience.
• Experience as an early infrastructure hire in a growing company.

Experience

• 5+ years of hands-on platform or infrastructure engineering experience in production environments.
• 3+ years of AWS experience at an architecture and design decision level, ideally across multiple accounts.
• 3+ years of production Kubernetes ownership. You've operated the cluster, not just deployed to one someone else ran.
• 3+ years of Terraform or equivalent infrastructure as code ownership in production.
• Proven production platform ownership. You've been on-call, you've been on the hook when it broke, and you've handled it.
• Hands-on ownership with AI systems in real production or commercial environments. Academic, hackathon, or side-project experience alone is not sufficient.

Compensation

Competitive base salary + equity + outcome-based performance bonus.