Description

You architect and deliver generative AI solutions for document interpretation, automated decision workflows, and enterprise governance.

This role is on-site.

Responsibilities

• Design agent-based workflows using LLMs, retrieval pipelines, and multi-agent orchestration frameworks including LangChain/LangGraph and Azure AI Agents.
• Build composite AI architectures combining LLMs, search, business rules, embeddings, and analytics with robust context pipelines.
• Develop backend components and API integrations for AI agents using Python, Azure AI services, Azure Functions, and APIM.
• Own production readiness including CI/CD, automated testing, monitoring, performance optimization, and adherence to responsible AI standards.

Required Skills

• 4-6 years of AI engineering experience, including leading GenAI initiatives from concept to deployment in enterprise environments.
• Strong proficiency in Python-based backend engineering with scalable APIs and microservices.
• Hands-on experience with Azure AI, Azure OpenAI, Azure Functions, and APIM for deploying AI capabilities.
• Deep understanding of RAG-style retrieval fundamentals including embeddings, vector search, chunking, prompting, and vector retrieval.
• Experience with LLM development for enterprise use cases.

Preferred Skills

• Experience with LangChain/LangGraph, Azure AI Agents, LlamaIndex, and Hugging Face Transformers.
• Vector database experience (Azure AI Search, Pinecone, FAISS) and MCP-based enterprise tool chains.
• Familiarity with multi-agent orchestration patterns such as tool-calling and DAG orchestration.

Key Skills

Education

Any Graduate