Gen AI Engineer

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 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 (Lang Graph, Auto Gen, 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