Gen AI Engineer

About the job

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 - 4-8 years Key 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 systems Must-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 throughput What 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.

Requirements

• Python
• Data Engineering
• Generative AI
• RAG architectures
• LLMs

Preferred Technologies

• Python
• Data Engineering
• Generative AI
• RAG architectures
• LLMs