Generative AI / Agentic AI Engineer (LLM + RAG + Knowledge Graphs)

Role Overview

Build real-world GenAI systems, not just demos. Work across LLMs, RAG, Graphs, and Agents. Opportunity to shape architecture and offerings from the ground up.

Responsibilities

• Build and deploy production-ready GenAI and Agentic AI systems using LLMs, RAG, and AI workflows.
• Develop scalable Python backends, APIs, and data pipelines for AI applications.
• Design RAG and hybrid search systems across vector databases, knowledge graphs, and unstructured data.
• Build agentic workflows using frameworks such as LangGraph, AutoGen, or CrewAI.
• Evaluate and optimize AI systems through prompt engineering, RAG evaluation, and model optimization.
• Translate business requirements into scalable, reliable, and production-ready AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3–8 years of experience in backend engineering, AI, or data-driven systems.
• Strong Python and backend development experience.
• Hands-on experience with LLMs, RAG pipelines, and AI system design.
• Experience working with APIs, data pipelines, and unstructured data.

Skills

• Python
• LLMs
• RAG
• LangGraph
• AutoGen