Lead/Staff Platform Engineer - Zencoder

About Zencoder

Zencoder is a universal AI platform focused on integrating generative coding workflows into existing developer tools and infrastructure. Connect any CLI to any IDE, starting with Claude Code, Codex, and Zen CLI, while leveraging Zencoder 's proprietary enterprise-grade features like multi-repo intelligence. The platform supports on-premise, hybrid, or cloud deployment, with air-gapped and zero-VPC options to maintain enterprise security. Through modular "Zen Agents," Zencoder codifies team practices into shareable, autonomous workflows that continuously code, test, and deploy.

The Opportunity

We're looking for an experienced engineer to raise the bar on how our organization builds, tests, ships, and operates software - for both human engineers and AI coding agents.

This is AI harness engineering: the discipline of making the fundamentals (CI/CD, testing, IaC, observability, secure delivery) so solid and well-shaped that agents can work productively inside them. Developer experience and platform engineering are a subset of that work. When the harness is good, humans ship faster and agents stop getting stuck on things that shouldn't be hard.

Security is inseparable from this. AI agents are accelerating both the pace and the shape of vulnerabilities, and secure delivery has to be built into the same stream as everything else - not bolted on.

Product teams own their services, pipelines, and tests. Your job is to raise the ceiling across the org - defining standards, building leverage, and helping teams level up their workflows, tooling, infrastructure, security posture, and necessary changes for AI Agents.

Key Responsibilities

This is a hands-on lead role - you'll set direction and be deep in the code, infra, and pipelines yourself. A lead here is very much a builder.

• Shape the platform and infrastructure that everything else runs on — the foundations product teams build on top of
• Improve the full dev loop: local development, CI/CD, deployment, and production feedback
• Define and drive standards around testing, IaC, observability, and secure delivery — and help product teams adopt them
• Build shared tooling, templates, and golden paths that create real leverage — paved roads teams actually want to use
• Own secure delivery end-to-end: unify security scanning, secrets management, dependency and supply-chain controls, and pen-testing workflows into the core pipeline so secure-by-default is the path of least resistance
• Stay ahead of the shifting security landscape as AI agents reshape both how vulnerabilities emerge and how they're exploited
• Shape repos, tooling, and conventions so coding agents can navigate them efficiently — clear structure, good test signal, fast feedback loops, well-scoped contexts, and docs agents can actually use
• Measure impact against DORA metrics and q