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Gen AI Consultant
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- Posted 2 days ago
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Job Description
Gen AI, Agent Frameworks, Agentic AI, RAG, MCP
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.
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)
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.
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)
More Info
Key Skills
Agent Frameworks
Claude
Pinecone
LangChain Agents
Azure OpenAI
Agentic AI solutions
LangGraph
RAG Retrieval-Augmented Generation
Vector Databases
LLM-based applications
ChromaDB
Microservices development
CrewAI
Generative AI
Azure AI Search API
Semantic Kernel
AutoGen
MCP Model Context Protocol
FAISS
Llama
OpenAI
Weaviate
