Principal GenAI Engineer

Location: Hyderabad
Employment Type: Full Time
Experience Level: Principal (8-14 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 Were Looking For

• 8-14 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
• Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
• Familiarity with CI/CD pipelines and DevOps practices

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

• Exposure to frontend frameworks (React, Next.js) for fullstack roles
• 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