- Full-time
Job Description
AI Context Developer
Location: Indianapolis, IN
Work Arrangement: Onsite/hybrid, client facing
Local candidates only
Position Overview
We are seeking hands on GenAI engineers to develop enterprise AI applications that securely use organizational data, documents, knowledge, and business context for our client. The developer will build context and retrieval layers that enable LLMs and AI agents to produce grounded, relevant responses within enterprise workflows. This role supports one of our client's business units, with potential to expand.
Key Responsibilities
- Build LLM applications, RAG pipelines, and agentic workflows.
- Build document ingestion, chunking, embeddings, and vector search.
- Implement retrieval and reranking, and design prompt and context engineering strategies.
- Build APIs and microservices that serve AI capabilities.
- Evaluate and monitor output quality, accuracy, and grounding.
- Apply enterprise security and governance controls to AI solutions.
- Meet business teams to identify what additional enterprise knowledge or data could enable new AI use cases.
- Contribute to the growth of the overall engagement.
Requirements
Required Qualifications
- Strong Python and LLM application development experience.
- RAG, embeddings, and vector search or vector databases.
- Prompt and context engineering.
- Document ingestion, chunking, retrieval, and reranking.
- APIs and microservices.
- LLM evaluation and agentic workflows.
- Comfortable meeting business teams and explaining AI solutions clearly.
- Must be local to Indianapolis, IN and able to work onsite.
Strongly Preferred
- Databricks, MLflow
- NVIDIA AI ecosystem
- LangChain, LangGraph, or LlamaIndex
- Knowledge graphs
- Enterprise security and governance
- Model serving and cloud AI platforms
- Regulated healthcare or pharma experience
Ideal Candidate
A technically strong, business aware GenAI builder who delivers grounded enterprise AI solutions and spots new ways AI can add value.
Requirements
Required Qualifications Strong Python and LLM application development experience. RAG, embeddings, and vector search or vector databases. Prompt and context engineering. Document ingestion, chunking, retrieval, and reranking. APIs and microservices. LLM evaluation and agentic workflows. Comfortable meeting business teams and explaining AI solutions clearly. Must be local to Indianapolis, IN and able to work onsite. Strongly Preferred Databricks, MLflow NVIDIA AI ecosystem LangChain, LangGraph, or LlamaIndex Knowledge graphs Enterprise security and governance Model serving and cloud AI platforms Regulated healthcare or pharma experience Ideal Candidate A technically strong, business aware GenAI builder who delivers grounded enterprise AI solutions and spots new ways AI can add value.