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Software Engineer; Agents & Operational Systems

Job in Green Bay, Brown County, Wisconsin, 54301, USA
Listing for: Self Fund Health
Full Time position
Listed on 2026-11-01
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer (Agents & Operational Systems)
Self Fund Health Software Engineer (Agents & Operational Systems) Remote
· Full time Company website Apply for Software Engineer (Agents & Operational Systems)

The Software Engineer (Agents & Operational Systems) architects, builds, and expands Self Fund Health’s fleet of LLM-powered agents - creating the tools, integrations, and data sources needed to automate complex health plan operations and superpower our clinical, operations, and account teams.

About Self Fund Health

Self Fund Health is a Wisconsin startup helping Midwest employers do something radical: buy healthcare instead of health insurance. For companies with 50+ employees, we pair transparent, upfront pricing with a clinical team of Nurse Navigators who guide members to high-value care — bending the cost curve in a state that ranks among the highest in the country for healthcare costs.

We're a small, fast-moving team where everyone has a real hand in rebuilding the health plan from the ground up, and where the work directly lowers costs for local businesses while improving care for the people who count on them.

Description
About Self Fund Health

Self Fund Health is a Wisconsin startup helping Midwest employers do something radical: buy healthcare instead of health insurance. For companies with 50+ employees, we pair transparent, upfront pricing with a clinical team of Nurse Navigators who guide members to high-value care — bending the cost curve in a state that ranks among the highest in the country for healthcare costs.

We're a small, fast-moving team where everyone has a real hand in rebuilding the health plan from the ground up, and where the work directly lowers costs for local businesses while improving care for the people who count on them.

Position Summary

Your primary mission is to iterate on our growing fleet of LLM agents and tooling. Day-to-day, that means executing the end-to-end engineering: you’ll build agent logic, tools, and prompt structures, integrate APIs and MCP servers, dive deep into conversations logs to spot areas for improvement.

Self Fund Health is betting heavily on practical AI agents to bend the administrative and clinical cost curve in healthcare. You’ll ship production-level LLM-based, human-in-the-loop tools and the software. That means you’ll need a keen understanding of the healthcare industry problems we’re solving, the ability to use LLM-assisted development tools and practices to efficiently create releasable software, awareness of the limits and risks of the technology we’re using, and consideration of how humans will interact with these tools through their lifecycle.

But “softwave engineer” in our startup environment isn’t limited to just coding and shipping agents. You’ll be collaborating with the small but mighty technology team across the stack to ensure the stability, security, and maintainability of the tools that run the company. This might mean contributing to our internal database and API/MCP tools layers, sharing best practices for local environment setup, tweaking website design and copy with our marketing team, or advising on how to configure a phone tree such that it creates automation opportunities.

Key Responsibilities
  • Design and Ship AI Agents: Build production-grade agents and multi-agent workflows on modern agent development frameworks (Google Cloud / Google Agent Developer Kit).
  • Curate Agent Tooling & Data Feeds: Take ownership of creating and improving APIs, data pipelines, search tools, and database connectors that feed context and execution power into our agent fleet.
  • Deep Healthcare Domain Grounding: Translate complex health plan concepts—plan designs, network tiers, copay structures, claims data, and clinical encounter feeds—ensuring agents operate within realistic bounds.
  • Ev…
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