Gen AI Engineer – RAG Systems, AI Transformation

November 13

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Gainwell Technologies

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Healthcare Insurance • Human Services • Healthcare

Gainwell Technologies is the nation’s leading provider of digital and cloud-enabled solutions across the human services and public health ecosystem. With a mission-driven approach, Gainwell serves clients in all 50 U. S. states, focusing on improving health outcomes and delivering intuitive, human-centered experiences. Their comprehensive suite of solutions includes Medicaid Enterprise modernization, data analytics, provider services, and pharmacy solutions, all designed to advance the future of healthcare and enhance community well-being.

10,000+ employees

⚕️ Healthcare Insurance

💰 Grant on 2023-06

📋 Description

• Enable the workforce to adopt an AI first strategy by leveraging AI code assistance tools • Architect and implement scalable RAG systems using Python and modern GenAI tools. • Build custom pipelines for document ingestion, chunking strategies, and embedding generation. • Evaluate and implement different embedding models (OpenAI, Azure OpenAI, Cohere, etc.) and chunking strategies (fixed-size, semantic-aware, overlap-based). • Create and optimize indexing strategies (vector, hybrid, keyword-based, hierarchical) for performance and accuracy. • Work with Azure AI Services, particularly Azure Cognitive Search and OpenAI integration, to deploy end-to-end AI applications. • Conduct AI enablement sessions, workshops, and hands-on labs to upskill internal teams on GenAI usage and best practices. • Participate in code reviews, contribute to best practices, and ensure the reliability, scalability, and maintainability of AI systems.

🎯 Requirements

• 5+ years of experience in software engineering • Strong expertise in Python • Proven track record of building and deploying RAG-based GenAI solutions • Hands-on experience with LlamaIndex, LangChain, or equivalent frameworks • Familiarity with prompt engineering, prompt tuning, and managing custom Copilot extensions • Strong understanding of LLMs, vector databases (like FAISS, Pinecone, Azure Cognitive Search), and embedding techniques • Solid knowledge of Azure AI, cloud deployment, and enterprise integration strategies • Proficiency with version control and collaborative development using GitHub.

🏖️ Benefits

• Professional development opportunities