Sr Software Engineer
Full Job Posting
We are unable to sponsor or take over sponsorship of an employment visa at this time
What You’ll Do:
Your primary focus is agent design and orchestration.
Multi-agent orchestration layer. Design and build the LangGraph-based system that classifies member intent and routes to the right agent. Stateful, context-preserving, failure-tolerant. Handles commercial agents and internally built capabilities through the same interface.
Agent integration contract. The standardized pattern that makes any agent pluggable: input schema, output schema, confidence signaling, latency SLA, fallback behavior. When the team integrates a new agent, they follow a pattern you designed.
Context management across turns. Multi-turn conversations that maintain full member context across agent handoffs. The member asks a follow-up two turns later; the platform knows what was said, which agent handled it, and what was retrieved.
Guardrail and safety layer. Clinical safety boundaries, PHI handling at the LLM layer, and response normalization ensuring every agent response arrives in a consistent tone and within compliance constraints regardless of which agent generated it.
RAG pipeline architecture. Benefits documents, formularies, and policy content retrieval via Azure AI Search. You define the ingestion strategy, chunking approach, hybrid search configuration, and retrieval quality standards.
Prompt architecture. Versioned prompt registry, structured output contracts, few-shot pattern design. Every prompt is testable, rollback-able, and understandable by the team.
To be considered for this position you must have:
Bachelor’s degree and 4-7 years of experience in software engineering.
Experience with agentic AI in production—not LLM wrappers, not single-agent chatbot demos, not RAG tutorials. Systems with multiple agents, explicit state management, and real users depending on the answers being correct.
2–3 years building and operating production LLM or agentic AI systems
You can describe specific decisions you made in a multi-agent system: state management approach, how you handled agent failures mid-conversation, how you kept the system governable as agents were added
LangGraph, AutoGen, or custom graph-based orchestration used in production, not just evaluated. You know where it breaks down and how you worked around it
Debugged retrieval quality problems, iterated on chunking strategies, dealt with stale knowledge bases in a live system with real users
Built evaluation systems from scratch: golden datasets, automated regression, domain-appropriate accuracy metrics. Your eval suite caught a production regression before users reported it
Experience in healthcare, insurance, fintech, or legal domains—AI systems where a wrong answer has consequences, and you designed the safeguards that make accuracy non-negotiable
Strong knowledge of Python. Work in an existing codebase and extend it with the AI layer
Azure OpenAI, Azure AI Search, Azure Container Apps are the target stack
The strongest candidates will also have:
Experience working in an Agile/Scrum environment.
Desire to think in a creative, lateral way both conceptually and in practical application.
You must be obsessed with addressing customer needs.
Strong communication and interpersonal skills.
Possess emotional intelligence.
The Stack
Python / FastAPI · LangGraph · Azure OpenAI / Claude via Azure · Azure AI Search · Azure Container Apps · LlamaIndex · LangSmith · Azure App Insights · PostgreSQL · Redis
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Other duties may be assigned.
Ready to make an impact? Join a team where your skills, attitude, and ideas are valued—and where you’ll help shape the future of healthcare technology.
Learn more about what makes BCBSNE such an exceptional place to work by visiting NebraskaBlue.com/Careers.
We strongly believe that diversity of experience, perspective and background will lead to a better workplace for our employees and a better product for our customers and members.
Qualifications
- Bachelor’s degree and 4-7 years of experience in software engineering.
- Experience with agentic AI in production—not LLM wrappers, not single-agent chatbot demos, not RAG tutorials. Systems with multiple agents, explicit state management, and real users depending on the answers being correct.
Responsibilities
- Your primary focus is agent design and orchestration.
- Multi-agent orchestration layer. Design and build the LangGraph-based system that classifies member intent and routes to the right agent. Stateful, context-preserving, failure-tolerant. Handles commercial agents and internally built capabilities through the same interface.
- Agent integration contract. The standardized pattern that makes any agent pluggable: input schema, output schema, confidence signaling, latency SLA, fallback behavior. When the team integrates a new agent, they follow a pattern you designed.
- Context management across turns. Multi-turn conversations that maintain full member context across agent handoffs. The member asks a follow-up two turns later; the platform knows what was said, which agent handled it, and what was retrieved.
- Guardrail and safety layer. Clinical safety boundaries, PHI handling at the LLM layer, and response normalization ensuring every agent response arrives in a consistent tone and within compliance constraints regardless of which agent generated it.
- RAG pipeline architecture. Benefits documents, formularies, and policy content retrieval via Azure AI Search. You define the ingestion strategy, chunking approach, hybrid search configuration, and retrieval quality standards.
- Prompt architecture. Versioned prompt registry, structured output contracts, few-shot pattern design. Every prompt is testable, rollback-able, and understandable by the team.
- Bachelor’s degree and 4-7 years of experience in software engineering.
- Experience with agentic AI in production—not LLM wrappers, not single-agent chatbot demos, not RAG tutorials. Systems with multiple agents, explicit state management, and real users depending on the answers being correct.
- 2–3 years building and operating production LLM or agentic AI systems
- You can describe specific decisions you made in a multi-agent system: state management approach, how you handled agent failures mid-conversation, how you kept the system governable as agents were added
- LangGraph, AutoGen, or custom graph-based orchestration used in production, not just evaluated. You know where it breaks down and how you worked around it
- Debugged retrieval quality problems, iterated on chunking strategies, dealt with stale knowledge bases in a live system with real users
- Built evaluation systems from scratch: golden datasets, automated regression, domain-appropriate accuracy metrics. Your eval suite caught a production regression before users reported it
- Experience in healthcare, insurance, fintech, or legal domains—AI systems where a wrong answer has consequences, and you designed the safeguards that make accuracy non-negotiable
- Strong knowledge of Python. Work in an existing codebase and extend it with the AI layer
- Azure OpenAI, Azure AI Search, Azure Container Apps are the target stack
- Experience working in an Agile/Scrum environment.
- Desire to think in a creative, lateral way both conceptually and in practical application.
- You must be obsessed with addressing customer needs.
- Strong communication and interpersonal skills.
- Possess emotional intelligence.
- The Stack
- Python / FastAPI · LangGraph · Azure OpenAI / Claude via Azure · Azure AI Search · Azure Container Apps · LlamaIndex · LangSmith · Azure App Insights · PostgreSQL · Redis
- To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Other duties may be assigned.
- Ready to make an impact? Join a team where your skills, attitude, and ideas are valued—and where you’ll help shape the future of healthcare technology.
- Learn more about what makes BCBSNE such an exceptional place to work by visiting NebraskaBlue.com/Careers.
- We strongly believe that diversity of experience, perspective and background will lead to a better workplace for our employees and a better product for our customers and members.
About Blue Cross and Blue Shield of Nebraska
Nonprofit Nebraska health insurer providing health, vision, dental, and travel coverage to groups, individuals, and families.
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