About Edra

Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.

We're a Series A startup, backed by Sequoia and other leading VC firms, led by Co-Founders who created and led Forward Deployed AI Engineering at Palantir, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.

The Role

We're looking for a Site Reliability Engineer to join our infrastructure team as the second-in-seat hire. Our team ships fast enough that we're starting to hit GitHub's rate limits, and infrastructure has to stay a month ahead of that. You'll be in key engineering meetings to ensure our infrastructure is ready before anyone asks, and to catch any decisions that may become infrastructure problems later.

This is not a ticket queue. You'll decide what gets built, push back when a managed service already does what someone wants to hand-roll, and invent when no pattern exists. You'll also write real software, not just the infrastructure code underneath it. We run containerized workloads on AWS and GCP, defined in infrastructure as code, with Postgres underneath. Some of our early infrastructure was built quickly before anyone owned it full-time. Part of the job is untangling that while keeping the team moving.

What You'll Do

Own our cloud infrastructure end to end: provisioning, security, reliability, and the infrastructure as code that defines it.

Stay ahead of the engineering roadmap and have infrastructure ready before features land, working directly with the founders on where the infrastructure goes next

Find where developers are waiting and remove the wait, whether that's CI, deployment, or environment spin-up. A person sat waiting is the most expensive thing we run, so rational spend on velocity is always on the table

Run the reliability practice: monitoring, logging, and alerting that fails loudly with a clear signal, and the response when it does

Lead large infrastructure builds and own our product security posture

Make the build-vs-managed-service call, and hold the line when the simpler path is the right one

Read and write Python well enough to see the infrastructure implications of what the team's building and catch problems before they land

Own AI model safety and the governance of agentic processes. The team leans on agents for repetitive work, and you make sure nothing unsupervised can act on production infrastructure

Hand capability to others, and support the team cross-functionally: build the tooling that lets engineers, GTM, the AI team, operations, and compliance do without you what today requires you

Keep current across cloud and model providers so that when an engineer brings a new announcement, you have a credible answer

What We’re Looking For

5 to 10 years in infrastructure, SRE, DevOps, or platform engineering

Deep, recent experience running production workloads on AWS or GCP, defined in infrastructure as code. A wide toolkit with one or two areas you go deep on. You won't know every service, and we expect you to learn fast

Python you've written in anger, in or alongside application code

Postgres in production, and containerized workloads running under an orchestration platform

A security instinct: you think about vulnerabilities continuously and patch constantly

Evidence that you've held down an infrastructure function alone or in a very small team

Work you can point to where you found an ambiguous problem, designed the fix, and made other people faster as a result

Comfort saying no to senior people when the infrastructure demands it

Bonus Points

GCP experience, especially migrations or multi-cloud rollouts

CloudWatch and GitHub Actions in your current stack

Time in a technical support or application support role earlier in your career