Senior Platform Engineer

Hi, we’re Gravie. Our mission is to create health benefits that actually benefit small and midsize businesses and their employees. Our innovative benefit solutions and services are developed and delivered by a diverse group of unique people. We encourage you to be your authentic self - we like you that way.

Gravie is seeking a Senior Platform Engineer to build and operate the platform our engineering teams ship on. AWS should be second nature: deep enough to reach for it before documentation, and you should be as comfortable working alongside AI agents as in a terminal.

The ideal candidate has genuinely operational AWS expertise, has worked in or closely with a platform team before, and knows a platform only succeeds when engineers choose it. They will own shared infrastructure, pipelines, and tooling end to end, partner with our architecture team on turning direction into paved paths teams actually adopt, and treat the engineers who use the platform as the customers they are.

At Gravie, engineers work closely with Product and own outcomes end to end, and we practice agentic development to increase the scope and leverage of that ownership: engineers use AI agents to help develop specs and plans, then to execute substantial multi-step engineering work, while setting guardrails and acceptance criteria and owning the quality of everything that ships. As agents take on more of the execution, the bar on problem framing, architectural judgment, system thinking, and risk identification gets higher, not lower.

If you have worked on a platform team, this will be familiar. If you have not, read it carefully, because it is the job.

• The platform is a product and engineers are its users. Adoption is the measure of success, not tickets closed. If teams route around something we built, that is our problem to solve, not their failure to comply.

• Self-service over gatekeeping. If the answer to a common request is a ticket to us, that is a bug in the platform.

• We pave roads, we do not police them. Standards belong in pipelines, templates, and defaults, not in reminders and review comments.

• Small team, wide surface. Leverage matters more than heroics, which is why AI tooling and automation are not side projects here - they are how the surface stays covered.

• We operate what we ship. On-call for platform services is ours. So is the postmortem, and so is fixing the class of problem rather than the instance.

• Documentation is a deliverable. A capability nobody can find or adopt without asking us is not finished.

• Build and operate the shared platform: CI/CD pipelines, service templates, deployment tooling, and the shared infrastructure services teams depend on.

• Own AWS infrastructure as code across multiple accounts, in Terraform, CDK, or both, held to the same standard as application code, including review, testing, and a real rollback story.

• Implement and sustain the paved paths teams build on, partnering with architecture on direction while owning the operational reality once a path is live.

• Operate what you build: on-call for platform services, incident response, the postmortem, and fixing the class of problem rather than the instance.

• Build observability in by default: metrics, logs, traces, SLOs, and alerts that page a human only when a human is actually needed.

• Own platform security posture alongside Security: identity and permission boundaries, secrets handling, network and data isolation, and remediation of findings in a HIPAA and SOC 2 environment.

• Make cloud spend attributable and defensible through tagging discipline, cost visibility, and removing waste before it compounds.

• Use AI agents as a normal part of daily workflow, and build them into the…