Principal GenAI Engineer

Job Description

About the Role:

\n
• 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.
\n
• 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.
\n

What We’re Looking For:

\n
• 8-14 years of experience in software engineering (backend or fullstack)
\n
• 2+ years of hands-on experience with LLMs (RAG, agents, prompt engineering)
\n
• Strong experience building production-grade distributed systems
\n
• Proficiency in Python
\n
• Strong experience with SQL & NoSQL databases
\n
• Hands-on experience with LangChain, LangGraph, or similar frameworks
\n
• Experience deploying systems on AWS / Azure / GCP
\n
• Strong understanding of APIs, microservices, and system design
\n
• Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
\n
• Familiarity with CI/CD pipelines and DevOps practices
\n

Key Responsibilities:

\n
• Design and build scalable GenAI applications using LLMs and RAG pipelines
\n
• Develop and optimize backend services and APIs for AI-powered systems
\n
• Build and deploy agent-based workflows and orchestration systems
\n
• Integrate LLMs into real-world enterprise applications
\n
• Ensure performance, scalability, and reliability of AI systems in production
\n
• Collaborate with product, data, and engineering teams to deliver end-to-end solutions
\n
• Implement monitoring, evaluation, and guardrails for GenAI systems
\n

Good to Have:

\n
• Exposure to frontend frameworks (React, Next.js) for fullstack roles
\n
• Understanding of model evaluation, fine-tuning, or LLMOps
\n
• Experience building multi-tenant or enterprise SaaS platforms
\n

Why Join Turing:

\n
• Work on cutting-edge GenAI use cases with global enterprises
\n
• Opportunity to build real-world AI systems at scale
\n
• High ownership and leadership in technical decision-making
\n