The inner loop. Replace shared, slow-to-provision environments with ephemeral ones an engineer can stand up on demand, and solve the multi-tenant test data seeding that makes them realistic enough to trust. Cut local build and test times. Establish golden paths: opinionated, documented ways to build, test, and run a service, so the answer to “how do I start” is one page and one command.
The path to production. Get us building an artifact once and promoting it across environments instead of rebuilding for each one, and give engineers a feature flag system they trust enough to pull deploy and release apart. Those two are what the rest of our continuous delivery plans are waiting on. Make dependency scanning, secrets detection, and static analysis default steps on every build, and move teams onto a common pipeline as we consolidate. We’re a small team and we’d rather adopt a good tool than write one, so knowing when to buy is part of the job.
The infrastructure underneath it. You’ll write the AWS and infrastructure-as-code that your tooling and our environments run on, working alongside the cloud engineers who own our production footprint, and carry the pager for what you build.
Tooling for AI-assisted development. Our engineers build with AI today, and generating code has gotten far cheaper than verifying it. You’d own pieces of what closes that gap: deterministic builds, test feedback fast enough to stay inside the loop, sandboxed execution, review gates for agent-authored changes, and platform capabilities exposed to agents through MCP.
At six months, a build runs once and that same artifact moves through every environment, and engineers have feature flags they rely on to deploy without releasing. At least one delivery team works against ephemeral environments with realistic seeded data.
Consolidated CI, observability that lets an engineer see their own system in production, and an internal developer portal follow from that foundation.