Gen AI Consultant

Responsibilities :

9-11 years of software engineering experience Strong hands-on expertise in Generative AI and LLM-based applications Experience designing and implementing Agentic AI solutions Hands-on experience with Agent Frameworks such as: LangGraph CrewAI AutoGen Semantic Kernel LangChain Agents Strong expertise in RAG (Retrieval-Augmented Generation) Experience implementing MCP (Model Context Protocol) Strong Python programming skills Experience with OpenAI, Azure OpenAI, Claude, Gemini, Llama, or similar LLMs Expertise in Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS, Azure AI Search) API and Microservices development experience Roles & Responsibilities Architect and build enterprise-grade Agentic AI platforms and solutions. Design multi-agent orchestration workflows for business use cases. Develop and optimize advanced RAG pipelines using enterprise knowledge repositories. Implement MCP-based integrations between AI agents, tools, and enterprise systems. Lead LLM solution design, deployment, scalability, and performance optimization. Build reusable AI accelerators, frameworks, and components. Guide development teams on GenAI best practices and AI architecture patterns. Collaborate with business stakeholders to define AI roadmaps and use cases. Ensure Responsible AI, security, governance, and compliance standards are followed. Mentor junior engineers and conduct technical reviews.

Additional Responsibilities:

Preferred Skills Azure OpenAI AWS Bedrock Databricks Mosaic AI GraphRAG Knowledge Graphs LLMOps/MLOps Docker & Kubernetes MLflow, LangSmith, PromptFlow CI/CD and Cloud Platforms (Azure/AWS/GCP)

Technical and Professional Requirements:

Gen AI, Agent Frameworks, Agentic AI, RAG, MCP