Generative AI Engineer

GenAI Developer/Engineer Experience: Total Experience: 10-15 years, AI-ML and GenAI Experience: 4–6 years Strong fundamentals and real‑world production exposure. Responsible for building, deploying, and operating GenAI solutions using modern agentic architectures. Core Responsibilities Design, develop, and deploy GenAI and ML solutions using Azure OpenAI, Azure ML, Azure AI Studio , and related services Build LLM‑powered applications using: Prompt engineering, Tool/function calling, Retrieval‑Augmented Generation (RAG) and Agentic AI design patterns Develop Agent‑to‑Agent (A2A) workflows for task decomposition, orchestration, and collaboration Implement Model Context Protocol (MCP) to standardize tool access, memory, and context management across agents Apply MLOps and LLMOps practices: CI/CD for models and prompts and Versioning, monitoring, evaluation Failure detection and mitigation (hallucinations, drift, prompt regressions) Implement LLM security and guardrails : Prompt injection prevention, Data leakage protection and Output moderation and policy enforcement Fine‑tune and adapt models for economy - token economics, latency, and cost optimization Build and expose AI capabilities via secure APIs and microservices Collaborate with architects, data engineers, and platform teams Actively research and document emerging GenAI techniques and tools Mentor junior engineers and contribute to internal knowledge assets Technology Stack Programming : Python (PEP8 / Google Python standards) LLMs : Azure OpenAI, OpenAI, open‑source and local LLMs AI Platforms : Azure ML, Azure Databricks, Azure AI Services Agent Frameworks : LangChain, LangGraph, Semantic Kernel (or equivalent) Protocols & Patterns : MCP, A2A, RAG variants DevOps : Docker, REST APIs, CI/CD pipelines Datastores : SQL‑based RDBMS, Vector databases Graph databases: Neo4j, GraphDB Soft Skills Strong ownership mindset and delivery focus Ability to work in agile, fast‑changing environments Effective collaboration across engineering and architecture teams