GHX is seeking a Software Engineer III to join Developer Platform & AI Enablement, the team that builds the tooling, standards, and AI capabilities the rest of GHX core product engineering runs on. Reporting to the Director, Software Engineering, Developer Platform & AI Enablement, you’ll work on a small team whose customers are other engineers: the developers building the healthcare supply chain products that take more than a billion dollars out of the cost of delivering healthcare every year.

The SWE III is responsible for analyzing, design, program, debugging, and modifying software.  This role is responsible for interacting with users to define system requirements and/or necessary modifications in an Agile/Scrum environment. You’ll grow into owning a capability end to end: a surface of the GHX agent platform, an MCP server other teams depend on, or the complexity-based router that decides whether a request runs on a local model or a hosted one. This is an embedded role, you’ll spend most weeks inside a product engineering team’s repository proving out a pattern before bringing the reusable version back to the broader engineering teams.

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.

Estimated Salary: $102,000 - $136,000

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