Security & Platform Engineer

InfrasAI is a fintech and insurtech company that helps financial services and insurance organizations use AI agents to build and quality-assure complex workflow mappings. The Security & Platform Engineer will own major platform, infrastructure, architecture, and security workstreams across a GitOps-driven Kubernetes environment, including deployment architecture, observability, reliability, resilience, and infrastructure security.

Responsibilities:

• 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

Requirements:

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