We are looking for a hands-on Senior AI / GenAI Engineer who combines strong Python engineering skills with practical experience building production-oriented RAG and Agentic AI solutions.

This is a builder role for an independent, self-driven engineer who can take ownership of a problem, understand the underlying business objective and cost implications, define a sensible technical approach, and drive the solution through implementation without requiring continuous direction.

Core Requirements

Python Engineering

• Strong hands-on Python programmingskills with a sound understanding of OOP and software engineering principles.
• Ability to write clean, modular, maintainable and production-quality code.
• Experience developing APIs using Python frameworks; FastAPI is preferred.

RAG

• Hands-on experience implementing an end-to-end RAG pipeline, covering data ingestion, retrieval, context preparation and response generation.
• Practical experience with retrieval techniques such as:
  • Hybrid search/retrieval
  • Reranking
  • Query rewriting
• Exposure to advanced RAG approaches such as Agentic RAG, Corrective RAG and HyDE.
• Understanding of RAG/LLM response evaluation, preferably using frameworks such as RAGAS or TruLens.

Agentic AI

• Hands-on experience building agent-based AI workflowsusing an orchestration framework, preferably LangGraph or equivalent.
• Strong understanding of agent workflow design, including nodes, edges, state management and orchestration.
• Experience integrating LLMs with tools/tool calling.
• Understanding or implementation experience with MCP (Model Context Protocol).

Graph Databases

• Practical hands-on experience with a graph database, such as Neo4j or equivalent.

Azure / Cloud

• Hands-on cloud implementation experience; Azure is preferred.
• Relevant experience may include:
  • Azure AI Search
  • Azure Cosmos DB
  • Azure AI Document Intelligence
  • Azure AI Foundry
  • Azure Application Insights

Added Advantage

Exposure to data engineering technologies such as:

• Apache Airflow
• PySpark
• Azure Data Factory

What We Specifically Look For

We are looking for someone with strong engineering ownership who can independently initiate and drive work rather than wait for detailed instructions.

The candidate should be able to:

• Understand the business problem and objectivebehind a technical requirement.
• Consider cost, budget and operational implicationswhen making engineering decisions.
• Independently structure the technical approach and drive implementation.
• Challenge or improve existing approaches when there is a better solution.
• Demonstrate strong coding and problem-solving ability, not just theoretical GenAI knowledge.
• Show genuine passion for engineering and AI, with evidence of personally building, experimenting and solving real-world problems.

This is not a purely theoretical or prompt-engineering role. We are looking for a strong programmer and hands-on AI engineer who can take GenAI solutions from problem definition through implementation and connect the technology to measurable business needs.