Enterprise GenAI Context Engineer

Zoho; Indianapolis (IN); Hybrid; USD 120,000 - 180,000; Full time

Job summary

RADcube is seeking a hands-on GenAI engineer in Indianapolis to develop enterprise AI applications that securely use organizational data, documents, knowledge, and business context. The role focuses on building context and retrieval layers enabling LLMs and AI agents to generate grounded, relevant responses within enterprise workflows.

The position is onsite/hybrid with client facing responsibilities, and local candidates only.

Qualifications

• Strong Python and LLM application development experience.
• Experience with RAG, embeddings and vector search.
• Proficient in prompt and context engineering.
• Experience with document ingestion, chunking and retrieval.
• Skilled in APIs and microservices.
• Ability to evaluate LLM outputs and design grounded AI solutions.
• Good at explaining AI solutions to business teams.
• Local to Indianapolis and onsite work required.

Responsibilities

• Build LLM applications, RAG pipelines and agentic workflows.
• Build document ingestion, chunking, embeddings and vector search.
• Implement retrieval, reranking and context engineering strategies.
• Develop APIs and microservices delivering AI capabilities.
• Evaluate output quality, accuracy and grounding.
• Apply enterprise security and governance controls to AI solutions.
• Collaborate with business teams to identify knowledge gaps for new use cases.
• Contribute to overall engagement growth.

Skills

Python development

LLM applications

RAG & embeddings

Prompt engineering

APIs & microservices

Business communication

Tools

LangChain

LangGraph

LlamaIndex

Databricks

MLflow

NVIDIA AI ecosystem

Job description

RADcube is seeking a hands-on GenAI engineer in Indianapolis to develop enterprise AI applications that securely use organizational data, documents, knowledge, and business context. The role focuses on building context and retrieval layers enabling LLMs and AI agents to generate grounded, relevant responses within enterprise workflows.

The position is onsite/hybrid with client facing responsibilities, and local candidates only.