Software Engineer III – Developer Platform & AI Enablement

Duties and responsibilities

• Analyzes, designs, programs, debugs, tests, documents, releases, and supports platform capabilities end to end.
• Authors technical designs and architectural artifacts, and reviews the designs of peers.
• Develops, versions, and documents reusable GitHub Actions and composite actions used across the organization.
• Develops, versions, and documents reusable terraform modules (or other IaC) used across the organization.
• Builds and operates MCP servers over stdio and remote/HTTP transports, owning tool schema design, transport selection, and authentication.
• Extends our internal agent platform, including the SDK and the APIs other GHX teams build against, and contributes to local model routing.
• Reads and safely modifies unfamiliar codebases, including Java and Maven builds, without owning the application code.
• Drives defects and blockers to resolution, and writes automated tests and system test specifications.
• Instruments developer-facing tooling to measure adoption and extends the team’s delivery-metrics pipeline.
• Participates in architectural design spikes, project planning, and estimation in an Agile/Scrum environment.
• Co-facilitates recorded AI in Automation Office Hours remotely each week.
• Facilitating live sessions, both remote and in person, is an essential function of this role.
• Actively uses AI-powered development tools to improve productivity and code quality, and authors the agent configuration artifacts other engineers reuse.
• Create and maintain documentation as part of development and enablement efforts.
• Stay up-to-date on industry trends and best practices related to Snowflake, Python, and AWS.
• May mentor and onboard new team members as needed.

Required Qualifications

• BS or MS Degree in Computer Science.
• Requires 3-5 years of software development experience
• Experience building internal tooling whose users were other engineers, with the ability to explain why a given tool was or was not adopted.
• Daily use of agentic coding tools — Claude Code (preferred), Copilot, Cursor, or similar.
• Direct experience authoring GitHub Actions at the reusable workflow or composite action level, or equivalent CI that other people consumed.
• Direct experience authoring Infrastructure as code.
• Technical writing that other engineers act on — design documents, ADRs, runbooks, or documentation you can point to.
• Willingness to teach live and unscripted, including co-facilitating recorded remote sessions and full-day in-person workshops.
• Willingness and ability to travel as needed.
• Must be able to work independently and as part of a team on multiple overlapping projects.

Preferred Qualifications

• Has measured a non-deterministic system and argued from the numbers — an eval harness, a benchmark, or a rubric.
• Experience building and operating MCP servers, including remote/HTTP transports and auth.
• Comfortable deploying and debugging on AWS
• An agent configuration artifact you authored that another engineer used — a skill, subagent, md/AGENTS.md, or MCP tool.
• Experience with local or open-weight inference: Ollama, llama.cpp, or MLX, quantization tradeoffs, context and KV-cache sizing, and OpenAI-compatible shims.
• Experience measuring developer outcomes: adoption instrumentation, DORA-style delivery metrics, and data plumbing behind messy organizational data.
• Experience with the healthcare supply chain, EDI documents and standards, an added advantage.