Software Engineer III – Developer Platform & AI Enablement

GHX

18h•$102,000 - $136,000

About The Position

GHX is seeking a Software Engineer III for its Developer Platform & AI Enablement team, which builds tooling, standards, and AI capabilities used by GHX core product engineering. Reporting to the Director, Software Engineering, Developer Platform & AI Enablement, this role serves internal engineering teams and works closely within product engineering repositories to prove out patterns before developing reusable versions for broader adoption. The engineer will grow toward end-to-end ownership of a capability such as part of the GHX agent platform, an MCP server, or a complexity-based model router. The role covers software analysis, design, programming, debugging, testing, documentation, release, and support. It includes developing reusable CI and infrastructure-as-code components; extending internal agent capabilities; supporting developer-facing tools and delivery metrics; and collaborating with engineering colleagues in an Agile/Scrum environment. The position also includes teaching and facilitating recorded remote office hours and live sessions, including in-person workshops. The role requires active use of AI-powered development tools and creating agent configuration artifacts for other engineers to reuse.

Requirements

Bachelor’s or master’s degree in Computer Science.
3–5 years of software development experience.
Experience building internal tools for other engineers and explaining why a tool was or was not adopted.
Daily use of agentic coding tools such as Claude Code, Copilot, Cursor, or similar; Claude Code is preferred.
Direct experience authoring reusable GitHub Actions or composite actions, or equivalent CI consumed by others.
Direct experience authoring infrastructure as code.
Technical writing used by other engineers, such as design documents, ADRs, runbooks, or documentation.
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.
Ability to work independently and collaboratively across multiple overlapping projects.

Nice To Haves

Experience measuring a non-deterministic system and drawing conclusions from the results, such as through an evaluation harness, benchmark, or rubric.
Experience building and operating MCP servers, including remote/HTTP transports and authentication.
Experience deploying and debugging on AWS.
An agent configuration artifact authored by the candidate and used by another engineer, such as a skill, subagent, md/AGENTS.md, or MCP tool.
Experience with local or open-weight inference, including Ollama, llama.cpp, or MLX; quantization tradeoffs; context and KV-cache sizing; and OpenAI-compatible shims.
Experience measuring developer outcomes, including adoption instrumentation, DORA-style delivery metrics, and data plumbing for organizational data.
Experience with healthcare supply chain, EDI documents, or standards.

Responsibilities

Analyze, design, program, debug, test, document, release, and support platform capabilities end to end.
Author technical designs and architectural artifacts, and review peers’ designs.
Develop, version, and document reusable GitHub Actions and composite actions for organizational use.
Develop, version, and document reusable Terraform modules or other infrastructure-as-code components.
Build and operate MCP servers using stdio and remote/HTTP transports, including tool schema design, transport selection, and authentication.
Extend the internal agent platform, including its SDK and APIs used by other GHX teams, and contribute to local model routing.
Read and safely modify unfamiliar codebases, including Java and Maven builds, without taking ownership of application code.
Drive defects and blockers to resolution, and write automated tests and system test specifications.
Instrument developer-facing tooling to measure adoption and extend the delivery-metrics pipeline.
Participate in architectural design spikes, project planning, and estimation in an Agile/Scrum environment.
Co-facilitate recorded AI in Automation Office Hours remotely each week.
Facilitate live sessions remotely and in person.
Use AI-powered development tools to improve productivity and code quality, and author reusable agent configuration artifacts.
Create and maintain documentation as part of development and enablement work.
Stay up to date on industry trends and best practices related to Snowflake, Python, and AWS.
Mentor and onboard new team members as needed.
Travel as needed.