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# Generative AI Engineer

- **Company:** Delaware Racing Association
- **Location:** Boston, MA, United States
- **Contract:** Temporary to permanent
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Data Security, Monitoring of Systems, Python (Programming Language), Knowledge-Based Systems, OpenAI, Search Technologies, Software Engineering, Data Processing, LangChain, Retrieval-Augmented Generation, Large Language Models, Llamaindex, Generative AI, Agentic-AI, Build Management, Containerization, Docker
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_1b20bca8edf9dc90f1a96b044e6f68d4

## About the Role

* Strong software engineering skills, ideally with significant Python experience
 * Experience building production applications using LLMs (OpenAI, Anthropic, or similar)
 * Experience building AI agents and multi-step agentic workflows
 * RAG, embeddings, semantic search, vector databases
 * Cloud infrastructure (AWS/Azure/GCP) and containerization (Docker)
 * A builder mentality: you'd rather ship a working prototype than write a deck about what could be built
 * Comfort operating with significant autonomy and ambiguity
 * Strong communication - able to explain technical concepts to non-technical senior stakeholders

Experience with LangGraph, LangChain, LlamaIndex or similar is useful, but we care more about your ability to design robust systems than any specific framework.

## Description

* Work directly with senior leadership on bottlenecks and repetitive processes
 * Translate business problems into clearly defined technical solutions
 * Design, build and deploy production-grade AI agents and applications
 * Build agentic workflows involving reasoning, retrieval, data processing and interaction with internal systems
 * Integrate LLMs with existing applications, documents, databases and third-party platforms
 * Build retrieval/knowledge systems (RAG) for internal company information
 * Implement evaluation, monitoring and observability for AI systems in production
 * Design human-in-the-loop processes where full automation isn't appropriate
 * Establish controls around data access, permissions and sensitive information
 * Measure impact - time saved, adoption, productivity gains, This is a rare opportunity to build an AI function from the ground up, with direct access to senior leadership and no legacy platform to inherit. The initial mandate is focused - deliver measurable value for the management company - but the trajectory is open-ended, with real potential to extend into the firm's wider portfolio!
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