Founding Engineer
Location: Remote
Role Overview
You will be one of the first engineers at DeepInspect. The architecture decisions you make will outlast the people who join later. The infrastructure you stand up is what customers will deploy into their own clusters. The features you ship go to real customers running real workloads in regulated environments.
DeepInspect is building infrastructure for governing AI systems in production. The gateway sits inline between users, agents, and AI applications and the LLMs they consume, enforcing identity- and data-aware policies in real time with sub-50ms overhead. Customers run it in their own Kubernetes clusters, which means engineering decisions show up in someone else's runbook.
This is a real ownership role. You see a problem, you fix it, you ship it. You disagree with a direction, you say so and we work through it. Less structure, fewer safety nets, more expected of you. When something breaks at 2am, you are the person who knows how it works because you built it.
This role reports directly to the CEO.
Key Responsibilities
- Architecture and Infrastructure: Make the foundational decisions that the rest of the engineering team will build on. Latency budgets, deployment topology, data flow, failure modes.
- Customer Deployments: Help customers deploy DeepInspect into their own EKS, AKS, or GKE clusters. Own the Helm charts, ingress and egress configuration, service mesh integration, and inter-service networking.
- Product Engineering: Ship features end to end across the gateway, policy engine, control plane, and frontend. Node.js and TypeScript on the server. React on the client.
- Production Operations: On-call for the systems you build. Investigate incidents, fix root causes, and feed learnings back into the platform.
- Engineering Standards: Define how the team writes code, reviews changes, tests, and ships. The bar you set is the bar future hires inherit.
Candidate Requirements
- Experience: 5+ years building and operating production systems. Less if the work speaks for itself.
- Kubernetes Depth: Real production experience with EKS, AKS, or GKE. Helm charts, service mesh, ingress and egress, inter-service communication. Comfortable walking a customer through a deployment in their cluster.
- System Design: You can reason about where latency comes from and how to control it. You know how to make decisions about consistency, throughput, and failure isolation, and you can defend them.
- Stack Fluency: Production experience with Node.js, TypeScript, and React.
- HTTP Fundamentals: Methods, headers, status codes, TLS, proxies, timeouts, streaming. The unglamorous details that determine whether an inline gateway works under real traffic.
- AI-First Workflow: You use AI tools effectively in your day-to-day engineering. You verify their output, and you know when to trust them and when not to.
- High Agency: You take ownership of problems and ship without waiting for direction.