Job Title: Senior Agentic AI Engineer / Generative AI Engineer ( Onsite -only W2)

Job Title: Senior Agentic AI Engineer / Generative AI Engineer

Location: Remote / Hybrid
Duration: Contract

Job Description

We are looking for a highly skilled Agentic AI Engineer with strong experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Multi-Agent Systems. The ideal candidate will design, develop, and deploy intelligent AI agents capable of autonomous reasoning, planning, tool usage, and workflow orchestration to solve complex business problems.

Required Skills

• 5+ years of experience in AI/ML, NLP, or Generative AI.

• Strong programming skills in Python.

• Hands-on experience with LLMs such as GPT-4, Claude, Llama, Gemini, or Mistral.

• Experience building RAG-based applications using vector databases such as Pinecone, FAISS, ChromaDB, or Weaviate.

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar Agentic AI frameworks.

• Knowledge of prompt engineering, embeddings, semantic search, and knowledge retrieval.

• Experience with REST APIs, tool calling, function calling, and agent orchestration.

• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Responsibilities

• Design and develop Agentic AI solutions using LLMs, RAG, and multi-agent architectures.

• Build intelligent AI agents capable of planning, reasoning, memory management, and tool execution.

• Develop and optimize RAG pipelines for enterprise knowledge retrieval and question-answering systems.

• Integrate AI agents with internal APIs, databases, and third-party applications.

• Implement prompt engineering, evaluation frameworks, and guardrails for AI systems.

• Deploy, monitor, and optimize AI applications in production environments.

• Collaborate with business and technical teams to deliver scalable AI-driven solutions.

Preferred Skills

• Experience with MCP (Model Context Protocol), AI Assistants, and Autonomous Agents.

• Knowledge of MLflow, Docker, Kubernetes, and MLOps/LLMOps practices.

• Experience with Databricks, Azure AI Studio, Vertex AI, SageMaker, or Bedrock.

• Exposure to AI governance, security, and responsible AI practices.

Keywords

Agentic AI, Generative AI, LLM, RAG, LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, GPT-4, Claude, Gemini, Pinecone, ChromaDB, FAISS, Vector Databases, Prompt Engineering, AI Agents, Multi-Agent Systems, Python, AWS, Azure, Google Cloud Platform, LLMOps.