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# Software Engineer

- **Company:** Prodigy Resources
- **Location:** Lincoln, NE, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Data Warehousing, Cursor, Python (Programming Language), OpenAI, Search Technologies, Single Sign-On, Software Engineering, TypeScript, Pinecone, LangChain, Retrieval-Augmented Generation, Large Language Models, Claude Code, Llamaindex, Backend, Build Management, Pgvector, Production Code, Weaviate, Azure OpenAI API, Claude, Google Gemini, Model Context Protocol, Agent2Agent Protocol
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/23_02C6885D0DBE8CC7F955022E06FB8D0A

## About the Role

8+ years in software engineering, with recent work shipping LLM-powered systems to production.

Required Skills

Strong Python, plus TypeScript or another backend language.

Hands-on work with LLM APIs from OpenAI, Anthropic (Claude), or Google (Gemini).

Experience with LangChain, LangGraph, LlamaIndex, Model Context Protocol (MCP), or the OpenAI Agents SDK.

Vector search with pgvector, Pinecone, or Weaviate.

Cloud deployment on AWS, Azure, or GCP, including Bedrock, Azure OpenAI Service, or Vertex AI.

You're comfortable in front of a customer's VP in the morning and in their codebase that afternoon.

Preferred Skills

Daily use of Claude Code or Cursor.

Agent-to-agent work using Google's A2A protocol.

Prior consulting, solutions engineering, or customer-facing engineering roles.

Experience with HIPAA or PII-regulated data.

## Description

You'll sit between the customer and the product team: scoping the problem, writing production code in Python, and getting it live. Remote, US-based.

Responsibilities

Work with customer engineering and business teams to scope AI use cases and decide what's worth building.

Build and deploy LLM applications: RAG pipelines, multi-step agents, and tool integrations over MCP.

Connect models to the customer's systems: APIs, databases, data warehouses, SSO.