Job Description
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
- 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
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