Principal GenAI Engineer - Backend- Hybrid (Marathalli)

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

Roles & Responsibilities

• Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

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