Staff 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.

ROLE SUMMARY

Gravie is seeking a hands-on Staff Platform Engineer to do three things at once: build the golden roads and paved paths our engineering teams build on, define the north star architecture the organization moves toward, and design and deliver our AI-enabled capabilities. This is the hub role for technical direction at Gravie: long-term architectural direction and the standards that carry it converge here and radiate outward across teams.

The ideal candidate combines deep distributed systems and AWS experience with real production generative AI experience, and is equally credible building a paved path teams voluntarily adopt and setting a target-state architecture the whole organization will inherit. They have established standards, reference implementations, and paved roads that engineers actually use, not just architecture documents. They will partner across Engineering, Product, Data, Security, and Infrastructure, and will work most closely with our Platform Engineering team, which is the primary vehicle for making change stick across the organization.

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.

This is a deliberately split role: roughly 40% golden roads and paved paths (hands-on, reference implementations, shared libraries, service templates, scaffolding, pipelines - a path isn't paved until a team other than yours has shipped on it), 30% north star architecture (published decisions that get adopted and enforced by tooling, not just written down), and 30% AI solutions (agent systems, retrieval and context design, evaluation, and guardrails). The mix shifts by quarter. Being the hub does not mean being the bottleneck - a good year looks like teams making more decisions on their own because direction and the paved path are clear enough to follow without asking. The role is planned and reviewed on this split, not funded out of leftover capacity; part of the job is saying out loud when the split is breaking toward a support desk.

KEY RESPONSIBILITIES

• Build the paved paths teams build on, including reference implementations, shared libraries, service templates, scaffolding, and pipeline templates, so the recommended way is also the easiest way.

• Treat the paved road as a product with real users: measure adoption and time to first success, and fix the parts people route around.

• Do the first real implementation yourself, on a real workload with a real team, not in a demo repository.

• Build the distributed systems patterns the paths encode: backend services, event-driven workers, job pipelines, APIs, and relational data models.

• Partner with the Platform Engineering team as the primary delivery vehicle - build paved paths with them, plan into their roadmap, and hand off sustaining ownership of what becomes shared infrastructure.

• Own migration and adoption, including moving existing services onto the path and retiring what it replaces.

• Stay in code review across teams and close to production incidents as primary evidence of where the path is failing.

• Define and publish the target-state architecture, with clear owners and decision dates, and keep it current as the business changes.

• Own the AWS foun