Generative AI Engineer

Role Overview

We are looking for a Generative AI Engineer to build optimize and productionise cutting-edge AI systems. You will focus heavily on backend AI orchestration framework integration and model this role you will take advanced RAG workflows and multi-agent concepts and turn them into scalable production-grade enterprise software.

Location- Bangalore Pune Chennai

Experience-4 to 7yrs

Key Responsibilities

• AI Orchestration: Build test and optimize bespoke Agentic AI solutions and multi-agent workflows.
• Core Product Integration: Co-develop integration pipelines to embed core AI models into client environments.
• Technical Delivery: Own the technical lifecycle of AI applications from rapid prototype to stable production release.
• Optimization & Debugging: Perform technical debugging root-cause analysis and latency/prompt optimizations.
• Best Practices: Implement engineering best practices for LLM evaluation guardrails and version control.
• Risk Management: Identify and flag model drift data leakage and system risks early.

Technical Requirements

• GenAI Ecosystem: 2 years of hands-on experience building production RAG pipelines and multi-agent systems using LangChain LangGraph or LlamaIndex.
• Protocols & Frameworks: Strong understanding of Model Context Protocols (MCP) A2A protocols and Agent Developer Kits.
• LLM Engineering: Practical proficiency in prompting techniques fine-tuning workflows and evaluating LLM outputs.
• Data Science Stack: Strong hands-on experience leveraging Python pandas scikit-learn and PyTorch.
• Cloud & MLOps: Experience deploying and scaling machine learning solutions on AWS Azure or GCP.
• DevOps & Containers: Working knowledge of Docker Kubernetes CI/CD pipelines and GitHub Actions.
• Backend Stack: Production-grade backend coding skills in Python with basic familiarity in JavaScript/TypeScript for API integrations.