Description

You will build and deploy generative AI applications and agentic automation workflows, owning the full lifecycle from model development to production integration.

This role is hybrid.

Responsibilities

• Build and deploy GenAI applications using LLMs like OpenAI, Azure OpenAI, Claude, Gemini, and Llama.
• Develop agentic AI workflows using CrewAI, AutoGen, LangGraph, or LangChain Agents.
• Design and implement RAG pipelines, vector search solutions, and embedding-based retrieval systems.
• Build scalable AI services using Python, FastAPI/Flask, and cloud platforms (Azure/AWS/GCP).
• Implement hallucination reduction, prompt engineering strategies, and model evaluation methods.

Required Skills

• 10+ years of experience in AI/ML, including model development, data preprocessing, EDA, training, and evaluation.
• 2+ years of hands-on experience in Generative AI (LLMs, embeddings, RAG, LLM-based apps).
• 6+ months of hands-on experience with Agentic AI frameworks (CrewAI, AutoGen, LangGraph, or LangChain Agents).
• Strong proficiency in Python and ML libraries (Scikit-learn, Pandas, NumPy).
• Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering.
• Familiarity with building scalable APIs using FastAPI, Flask, or Django.
• Hands-on knowledge of cloud services (Azure/AWS/GCP) for AI deployment.
• Strong understanding of REST APIs, microservices, and integration patterns.
• Experience with Git, CI/CD, Docker, and model deployment best practices.

Preferred Skills

• Experience with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search.
• Ability to monitor, evaluate, and optimize GenAI models for accuracy, performance, and cost.

Key Skills

Education

Any Graduate