AI Developer

Job highlights

• Shift timing : 3:00 PM - 12:00 AM
• Work from office only
• Experience : 3 Years
• Good Communication
• Skills : Gen AI,Python,LLM,Rag,Machine learning . We are seeking a skilled AI Engineer with 3 years of hands-on experience in building intelligent,automated,and agentic AI solutions

Role : AI / ML Engineer
Location : Chennai ( Maduravoyal)
Experience : 3 Years
Notice Period : Immediate
Open Position : 2
Work from office only
Shift timing : 3:00 PM - 12:00 AM
Good Communication
Skills : Gen AI , Python, LLM, Rag, Machine learning

We are seeking a skilled AI Engineer with 3 years of hands-on experience in building intelligent, automated, and agentic AI solutions. The ideal candidate will have strong expertise in workflow automation using n8n, Microsoft Azure AI Foundry, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and the design of AI Agents and Agentic AI systems. You will play a key role in designing, developing, and deploying enterprise-grade AI solutions that drive automation, intelligence, and decision-making across business workflows.

Key Responsibilities

Design, develop, and deploy AI-powered automation workflows using n8n, integrating multiple APIs, databases, and AI services.
Build, fine-tune, and deploy LLM-based applications using Azure AI Foundry, including model selection, prompt engineering, and evaluation.
Develop and optimize RAG pipelines using vector databases (eg, Azure AI Search, Pinecone, Weaviate, FAISS, Chroma) for context-aware AI applications.
Design and implement AI Agents and Agentic AI systems capable of multi-step reasoning, tool use, memory, and autonomous decision-making.
Integrate LLMs (OpenAI GPT, Claude, Llama, Mistral, Azure OpenAI) into business applications via APIs, SDKs, and orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI).
Build end-to-end AI pipelines covering data ingestion, embedding generation, vector storage, retrieval, prompt orchestration, and response generation.
Collaborate with cross-functional teams (Product, Data, DevOps, QA) to translate business requirements into scalable AI solutions.
Implement observability, evaluation, and guardrails for AI systems including prompt safety, hallucination control, and cost optimization.
Deploy AI solutions on Microsoft Azure using Azure AI Foundry, Azure OpenAI Service, Azure Functions, Azure Container Apps, and Azure DevOps Pipelines.
Maintain documentation for architecture, prompts, models, and deployment processes.

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