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Principal GenAI Engineer (FS/BE)

Summary

Lead enterprise-scale GenAI projects for Fortune 500 clients, designing and building scalable LLM-powered systems with RAG, agents, and Graph-RAG architectures.

No. of positions: 1
Remote/India, EST overlap 4 hours
Full Stack/Backend development experience
Immediate- 1week availability
About the Role

Turing is hiring a Principal GenAI Engineer with strong expertise in LLMs to lead enterprise-scale AI implementations for Fortune 500 clients. This role focuses on building Graph-powered RAG systems (Graph-RAG) that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.

Principal GenAI Engineer – Backend / Fullstack

Location: Remote
Employment Type: Full Time
Experience Level: Principal (10-14 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 We’re 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

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

See also