Infrastructure Engineer

Counsel

Counsel's mission is to multiply the world's healthcare capacity. We believe in a future in which every person has a personalized, AI-enabled doctor always in their pocket. To accomplish this, we're building the first fully-vertical, AI-native medical group from the ground up. We've redesigned the entire clinical stack with custom AI tools that make our in-house physicians 10x faster and smarter.

Since our founding in 2023, we have formed partnerships with leading healthcare organizations and are on track to serve hundreds of thousands of patients on our platform within the next year. We have raised over $35M from a16z, Google Ventures, Pear VC and other top-tier VC firms. Our team combines deep expertise in medicine (Harvard, Mt. Sinai, Mass General, UCSF) and technology (MIT, Google, Deep Mind, NVIDIA, Stripe, Meta) — and we're looking for exceptional people to join us as we scale.

Join us as we build the future of AI in healthcare!

At Counsel, we've built a product that patients and physicians love, on a fast-moving stack. As we scale, the line between "application code" and "infrastructure" keeps blurring and we need someone who lives right at that intersection.

We're looking for a Backend Infrastructure Engineer who's equal parts software engineer and infrastructure engineer. You won't be sitting in a silo writing Terraform all day, and you won't be shipping product features in React. You'll own the layer in between: the CI/CD pipelines, the IaC that provisions our AWS environment, the backend services that glue our systems together, and the developer tooling that keeps a fast-growing engineering team moving.

• Shape our infrastructure-as-code. Develop and maintain our cloud infrastructure using Terraform.

• Build and improve CI/CD. Own our build, test, and deployment pipelines end to end. Your goal is to make deploying to production boring; fast, reliable, automatic.

• Write real backend code. Contribute production backend services and core server-side systems. You write application code, rather than simply orchestrating it.

• Build our core archetypes. Create production-grade patterns for new deployments, jobs, consumers, and workers. Think: an abstract base stream consumer or cron executor built for reuse across the team.

• Make other engineers faster. Improve local dev workflows, cut build times, kill flaky infrastructure, and build the internal tools people actually want to use.

• Strengthen security and compliance. Work closely with our security and compliance team to harden our infrastructure posture — secrets management, IAM policies, network isolation, and audit logging in a HIPAA-regulated environment.

• Just as comfortable in an IDE writing application code as in a terminal managing cloud infrastructure, because backend and infra aren't separate disciplines to you.

• Already scripting the fix by the third time you'd otherwise have to do something manually.

• Understands how a request travels from a user's browser through a load balancer, into a container, to a database, and back, and can debug any layer along the way.

• Reaches for the right tool over the trendy one and would rather ship something working today than architect something perfect next quarter.

• Can explain infrastructure decisions to product engineers and translate product requirements into infrastructure changes.

• 3–5 years of professional experience in backend engineering, infrastructure engineering, or a mix of both.

• Strong proficiency in at least one strongly-typed or compiled language (Go, Rust, Java, Typed Python, Type Script, etc.).

• Experience with AWS, GCP, or Azure cloud services.

• Familiarity with containerized environments and Docker.

• Hands-on experience writing and maintaining Terraform (or equivalent IaC tooling).

• A track record building and maintaining CI/CD pipelines (Git Hub Actions, CircleCI, or similar).

• Kubernetes experience.

• Experience with Type Script/Node.js.

• Experience working in a regulated environment (HIPAA, SOC 2, etc.).

Our backend platform is built to support large-scale AI-driven clinical systems and enterprise integrations.

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