Generative AI Engineer

What you'll work on

At least 1+ year Hands-on experience with agentic AI frameworks (e.g. LangGraph, Strands Agent, ADK) for building multi-step reasoning and tool-using agents

Familiarity with integrating Model Context Protocol (MCP) into AI workflows

Experience building evaluation frameworks for AI systems (retrieval quality, agent performance, LLM outputs)

Experience in designing and implementing information retrieval systems using embeddings, vector stores (e.g. Milvus, Qdrant), or similarity match & ranking techniques

Comfortable working within Linux/Unix environments

Expert Python programming experience

Experience building generative AI applications using LLMs and vector databases

Knowledge of current Gen AI research and techniques in one or more of the following areas: RAG systems, Agentic AI (multi-agent orchestration, tool calling), or Prompt Engineering

Experience in building Rest and GraphQL API endpoints for Agent backend

Designing and implementing generative AI systems including multi-agent workflows, tool calling architectures, LLM orchestration patterns, and reusable AI components

Building agentic AI solutions that coordinate multiple AI services and tools to solve complex domain-specific problems

Designed and optimized RESTful services