Software Engineer III – Developer Platform & AI Enablement

globalhealthcareexchangeinc; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

globalhealthcareexchangeinc is seeking a software engineer to build and improve developer tools, shared platform capabilities, and AI features used by product engineering teams. You will collaborate within product codebases to validate patterns and turn successful approaches into reusable capabilities, potentially owning parts of an internal agent platform or tool server over time.

The role requires designing and delivering end-to-end platform software, implementing CI workflows, and developing

Qualifications

• Bachelor's or master's degree in computer science and 3-5 years of software development experience.
• Experience creating internal tools for engineers and evaluating why teams adopt or reject them.
• Daily use of agentic coding tools such as Claude Code, Copilot, Cursor, or similar.
• Hands-on experience authoring reusable GitHub Actions or equivalent shared CI, and infrastructure as code.
• Technical writing that engineers use, such as design documents, architecture decisions, runbooks, or product documentation.
• Ability to teach live, work across concurrent projects, and travel as needed.

Responsibilities

• Design, build, test, document, release, and support platform software end to end.
• Create reusable CI workflows and infrastructure-as-code modules for engineering teams.
• Develop and operate MCP servers, including tool schemas, transport choices, and authentication.
• Extend an internal agent platform and its SDK and APIs, and contribute to routing between local and hosted models.
• Safely navigate unfamiliar codebases, including Java and Maven projects, to validate platform patterns.
• Write automated tests and system test plans, resolve defects, and measure adoption of developer tools.
• Contribute to technical designs and planning, document practices, and co-lead live training sessions.

Skills

Agentic coding tools

GitHub Actions

Infrastructure as code

Java

Education

Bachelor's or Master's in Computer Science

Tools

MCP servers

AWS deployment

open-weight inference

Job description

Role overview

Build and improve the developer tools, shared platform capabilities, and AI features used by product engineering teams. The work is both embedded and reusable: you will collaborate within product codebases to validate patterns, then turn successful approaches into capabilities other teams can adopt. Over time, you may own a distinct part of an internal agent platform, a tool server, or model-routing functionality.

Responsibilities

• Design, build, test, document, release, and support platform software end to end.
• Create reusable CI workflows and infrastructure-as-code modules for engineering teams.
• Develop and operate MCP servers, including tool schemas, transport choices, and authentication.
• Extend an internal agent platform and its SDK and APIs, and contribute to routing between local and hosted models.
• Safely navigate unfamiliar codebases, including Java and Maven projects, to validate platform patterns.
• Write automated tests and system test plans, resolve defects, and measure adoption of developer tools.
• Contribute to technical designs and planning, document practices, and co-lead live training sessions.

Requirements

• Bachelor's or master's degree in computer science and 3-5 years of software development experience.
• Experience creating internal tools for engineers and evaluating why teams adopt or reject them.
• Daily use of agentic coding tools such as Claude Code, Copilot, Cursor, or similar.
• Hands-on experience authoring reusable GitHub Actions or equivalent shared CI, and infrastructure as code.
• Technical writing that engineers use, such as design documents, architecture decisions, runbooks, or product documentation.
• Ability to teach live, work across concurrent projects, and travel as needed.

Nice to have

• Experience with MCP servers and remote HTTP transports, AWS deployment and debugging, local or open-weight inference, evaluation or benchmarking of non-deterministic systems, or agent configuration artifacts used by other engineers.