Job Description

Job Description We are seeking a hands‑on AI Engineer to build, and deploy agentic AI solutions, including tool‑using LLM agents, autonomous workflows, and multi‑agent systems. The candidate should have strong engineering fundamentals, practical experience with LLM‑based development, and a solid understanding of integrating agents with enterprise systems via APIs, RAG pipelines, vector databases, orchestration frameworks, and the Model Context Protocol (MCP). Candidate will collaborate with AI Architect/s, Vertical teams, and domain experts to translate business problems into scalable, production-ready AI automations. The role involves implementing, and operating stateful, multi-agent systems using LangChain and LangGraph, fully integrated within the Azure AI and multi-cloud ecosystem under strict enterprise governance. Must have skills: Agentic AI Frameworks & Platforms - Experience with modern agentic and orchestration frameworks such as: - LangChain, LangGraph, Microsoft Foundry - Databricks AI/BI Genie, Mosaic AI Agent Framework - Snowflake Cortex AI - AWS Bedrock AgentCore - Google Vertex AI Agent Builder, Google ADK - Other comparable Agentic AI frameworks and services Hands-on expertise in: - MCP (Model Context Protocol), A2A (Agent-to-Agent) workflows, Swarm agent architecture pattern - Vector Databases, Vector Search, Embeddings - Long-Term & Short-Term Memory integration - Tool Calling & Function Calling pipelines - LLM integration, tuning, and orchestration - Logging & tracing for agent actions - Containerize and deploy solutions on cloud environments (Azure / AWS / GCP) Good to have skills: - Deep understanding of machine learning, deep learning, Agentic AI Architectures - Knowledge of data governance, security, and compliance in cloud environments