Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Robert Half via LinkedIn
Position Intel: This is a hands-on applied AI position where you’d partner closely with the AI Architect to build and operationalize AI agents and automation workflows across the organization. The role focuses heavily on retrieval-augmented generation (RAG), agent frameworks, and LLM evaluation, all within a Databricks-centric data platform and Microsoft Copilot Studio ecosystem.
You’d be responsible for building and deploying AI agents, configuring embeddings/vector retrieval strategies, and developing prompt logic to ensure accurate, grounded responses. A big part of the role also involves evaluating and auditing agent performance—identifying issues like hallucinations or retrieval gaps and improving reliability over time. On the data side, you’d work with teams to prepare and structure data for AI workflows in Databricks, including document ingestion, chunking, and indexing.
They’re looking for someone with ~2–5 years of experience in applied AI, ML engineering, or data science, strong Python skills, and familiarity with RAG workflows, vector databases, or LLM evaluation. Experience with Databricks, Azure, or Microsoft Copilot Studio would be a big plus.
Requirements:
- Python + Applied AI/ML experience (2–5 years building ML or AI solutions)
- RAG / LLM experience – embeddings, vector databases, and prompt engineering
- Databricks or cloud data platforms
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Source: Robert Half careers (LinkedIn)