Generative AI Engineer - RAG/LangGraph

Years of experience : 4-8 years

Relevant experience : 3+ years in Gen AI

Mandatory skills :

- Strong hands-on experience in Python development

- Strong understanding of AI and Generative AI concepts

- Experience building agentic AI solutions

- Hands-on experience with Python ADK or similar agent development frameworks

- Good understanding of prompt engineering

- Ability to write effective instructions for agents and define agent behaviors

- Experience with agentic flows and orchestration patterns

- Working knowledge of MCP (Model Context Protocol)

- Experience with RAG techniques

- Familiarity with MLflow or similar ML lifecycle tooling

- Exposure to LangGraph or graph-based orchestration frameworks

- Good understanding of Agile and Agile team ways of working

- Strong debugging, problem-solving, and Python coding skills

Good to have:

- Experience in Big Data ecosystems

- Hands-on experience with PySpark

- A complementary secondary skill aligned to the primary AI/Python skillset, such as data engineering, cloud, or MLOps

- Exposure to scalable data processing pipelines

- Familiarity with deploying AI workloads in enterprise :

- Design, build, and enhance AI and Generative AI solutions using Python

- Develop and manage agentic workflows for complex task execution

- Create effective prompts, system instructions, and agent interaction patterns

- Build AI applications using Python-based tools, frameworks, and ADKs

- Work with MCP, agent/tool integration patterns, and orchestration frameworks

- Implement and manage RAG-based techniques for context-aware AI use cases

- Use MLflow or similar tools to support experiment tracking and model lifecycle workflows

- Collaborate in an Agile delivery environment with cross-functional teams

- Translate business requirements into scalable AI-enabled solutions

- Support testing, debugging, and optimization of Python-based AI applications

(ref:hirist.tech)