Collective Health

Healthcare

LeadSoftwareEngineer,AgenticAISystems

$138–173k Lehi, Utah, United States; Plano, Texas, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Software Engineer, Agentic AI Systems at Collective Health. Skills: Agentic AI, LLM Behaviors, Python Development, Google Cloud Platform. Execute Agentic Workflows. Build AI agents”

What You'll Achieve.

Automate complex claims workflows; Provide factual, data-driven responses; Handle claims logic with high precision; Improve domain-specific performance; Ensure agents pause, persist state, resume workflows; Intercept non-compliant agent behavior; Intercept toxic/hallucinated outputs; Ensure PHI is never exposed

Industry & Context.

Healthcare
Problems you'll solve

Root cause analysis; Troubleshooting

Eligibility Requirements

In office 2 days/week

What They're Looking For.

Must Have

Expert Python Developer, 8+ years Full-Stack experience, Hands-on Gemini experience, Hands-on Vertex AI experience, Hands-on Agent SDK experience, Experience with LangChain, Experience with LangGraph, Experience with PydanticAI, Experience with Vertex AI Python SDK, Experience with Reasoning Engine, Experience with Vertex AI Extensions, Experience with Vertex AI Function Calling, Experience with prompt engineering, Experience with AI-enhanced development tools

Nice to Have

Familiarity with healthcare interoperability, Familiarity with claims data structures, Practical LLM fine-tuning experience, Working knowledge of Java, Working knowledge of Spring Cloud

What You'll Do.

Execute Agentic Workflows

Develop agent behaviors

Optimize agent behaviors

Implement RAG strategies

Implement grounding strategies

Design system instructions

Implement few-shot prompting

Implement Chain-of-Thought reasoning

Perform Supervised Fine-Tuning

Improve domain-specific performance

Understand architectural decisions

Drive reusable patterns

Design Stateful Orchestration patterns

Implement human review breakpoints

Implement Input/Output Guardrails

Implement 'Circuit Breaker' logic

Detect non-compliant agent behavior

Intercept toxic outputs

Intercept hallucinated outputs

Implement Google Cloud DLP

Ensure PHI is not exposed

How You'll Work.

Team & Collaboration

Cross-functional teams; Agentic AI strategy

Process & Methodology

AI-First SDLC

Full Job Description

At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design. The Claims AI Automation team is currently evolving from traditional rule-based adjudication to an intelligence-driven platform. We are seeking a Lead Software Engineer who excels at high-level technical execution. This role is focused on the development and delivery of our Agentic AI strategy, turning architectural blueprints into production-ready systems. The ideal candidate will be the primary engine for building Python-based AI agents using the Google Cloud (GCP) ecosystem to automate complex claims workflows. You will be responsible for implementing sophisticated LLM behaviors using Gemini. What you will do: Execute Agentic Workflows: Build and deploy sophisticated AI agents using Google Vertex AI and the Google Agent SDK (ADK) based on provided architectural specifications. Develop and optimize agent behaviors using Gemini (Pro/Flash) with a focus on reliable tool-calling and multi-step reasoning; implement RAG and grounding strategies to ensure AI agents provide factual, data-driven responses derived from internal claims databases and policy documents. Design and implement complex system instructions, few-shot prompting, and Chain-of-Thought reasoning to ensure agents handle claims logic with high precision, performing Supervised Fine-Tuning on Gemini models to improve domain-specific performance in adjudication and medical coding Data & Messaging: Expert in SQL/PostgreSQ/AlloyDB/BigQueryUnderstand architectural decisions and actively drive reusable patterns for cloud-native, AI-enabled backend systems. Design and implement Stateful Orchestration patterns that incorporate human review breakpoints, ensuring agents can pause, persist state, and resume workflows after auditor approval. Implement Input/Output Guardrails and 'Circuit Breaker' logic

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