Principal GenAI Engineer (Backend/Fullstack) - 78771

Location: Mumbai (3 Days WFO) Employment Type: Full Time Experience Level: Principal (5-9 years) About the Role: Turing is hiring a Principal GenAI Engineer to lead enterprise-scale AI implementations for Fortune 500 clients. This role focuses on designing and building scalable, production-grade GenAI systems powered by LLMs, Retrieval-Augmented Generation (RAG), and agent-based architectures. You will work at the intersection of backend/fullstack engineering and applied AI , building reliable, high-performance systems that integrate LLM capabilities into real-world applications.

What We’re Looking For: 5-9 years of experience in software engineering (backend or fullstack) 2 years of hands-on experience with LLMs (RAG, agents, prompt engineering) Strong experience building production-grade distributed systems Proficiency in Python Strong experience with SQL & NoSQL databases Hands-on experience with LangChain, LangGraph, or similar frameworks Experience deploying systems on AWS / Azure / GCP Strong understanding of APIs, microservices, and system design Key Responsibilities: Design and build scalable GenAI applications using LLMs and RAG pipelines Develop and optimize backend services and APIs for AI-powered systems Build and deploy agent-based workflows and orchestration systems Integrate LLMs into real-world enterprise applications Ensure performance, scalability, and reliability of AI systems in production Collaborate with product, data, and engineering teams to deliver end-to-end solutions Implement monitoring, evaluation, and guardrails for GenAI systems Good to Have: Experience with vector databases (Pinecone, Weaviate, FAISS, etc.) Exposure to frontend frameworks (React, Next.js) for fullstack roles Familiarity with CI/CD pipelines and DevOps practices Understanding of model evaluation, fine-tuning, or LLMOps Experience building multi-tenant or enterprise SaaS platforms Why Join Turing: Work on cutting-edge GenAI use cases with global enterprises Opportunity to build real-world AI systems at scale High ownership and leadership in technical decision-making