Responsibilities

Build reusable AI and ML solutions including Document Intelligence, RAG pipelines, summarization, classification, and anomaly detection
Design and train custom Document Intelligence neural models
Implement RAG architectures using Azure AI Search with hybrid retrieval and semantic ranking
Develop LLM reasoning workflows using Azure OpenAI and Azure AI Foundry
Build agent orchestration workflows with tool-use and confidence-based routing
Create evaluation frameworks, drift detection, and HITL review systems
Implement audit trails, prompt/response logging, and SOC 2 aligned AI workflows
Monitor AI model performance, accuracy, and operational costs
Mentor engineers on prompt engineering, RAG, and AI architecture best practices

Required Skills

5–8 years of engineering experience with 3+ years in AI/ML systems
Strong expertise in Azure OpenAI, Azure AI Foundry, AI Search, and Document Intelligence
Experience with GPT-4o, GPT-4o-mini, RAG architectures, semantic ranking, and prompt engineering
Strong Python programming skills for AI/ML development
Experience with LangChain, LangGraph, Semantic Kernel, or similar frameworks
Hands-on experience with Document Intelligence custom neural models
Knowledge of vector databases, embeddings, and Medallion architecture
Experience with audit trails, drift detection, and AI governance in regulated environments
Familiarity with Git, IaC, and trunk-based development
Strong analytical, troubleshooting, and communication skills