Job Title

We are looking for a hands-on Gen AI Engineer with a strong Python and Data Engineering background, who has real-world experience building, deploying, and scaling Generative AI solutions. This role requires practical exposure—not theoretical knowledge or certification-only experience. Experience Range - 3-8 yearsKey Responsibilities- Design, build, and deploy production-grade Gen AI solutions - Develop and optimize RAG (Retrieval-Augmented Generation) pipelines - Build and manage Agentic AI workflows for autonomous task execution - Integrate LLMs (LLaMA, OpenAI, Claude, etc.) into business applications - Work with vector databases for embedding storage and retrieval - Handle real-time inference pipelines and low-latency AI services - Collaborate with data engineers, backend teams, and product stakeholders - Ensure scalability, monitoring, and performance optimization of Gen AI systemsMust-Have Skills- Strong Python (production-level coding experience) - Data Engineering background (ETL/ELT, pipelines, APIs, data processing) - Hands-on Gen AI experience in real projects (not POCs alone) - RAG architectures – end-to-end implementation - Agentic AI frameworks (LangGraph, AutoGen, CrewAI or similar) - LLMs: LLaMA (preferred), OpenAI, Hugging Face models - Vector Databases: FAISS, Pinecone, Weaviate, Milvus, Chroma - Prompt engineering with versioning and evaluation - API development (FastAPI / Flask)Good to Have- MLOps exposure (Docker, CI/CD, model deployment) - Experience with real-time streaming or async systems - Cloud exposure: AWS / Azure / GCP - Experience optimizing latency, token cost, and throughputWhat We Do NOT Want- Purely theoretical Gen AI knowledge - Certification-only profiles without real project implementation - Fresh Gen AI learners without backend or data engineering foundation