Principal GenAI Engineer

Principal GenAI Engineer – (Knowledge Graphs Good to Have)

Employment Type: Full Time
Location: Bangalore (Hybrid – 3 days in office)
Experience Level: Principal (8–13 years)

About Turing

Turing, based in Palo Alto, California, is the world’s first AI-powered tech services company. It has reimagined tech services by combining AI-vetted talent, AI-accelerated development, and access to world-class AI experts who have built some of Silicon Valley’s most iconic companies.

Founded in 2018, Turing has scaled rapidly with over 2 million developers on its Talent Cloud and 900+ global clients. The company has been recognized by Forbes, The Information, and Fast Company as one of the most innovative companies globally.

About the Role

Turing is looking for a Principal GenAI Engineer to lead enterprise-scale AI initiatives for Fortune 500 clients. This role will focus on designing and deploying production-grade GenAI systems, including advanced RAG pipelines, agent-based architectures, and scalable LLM applications.

You will work closely with cross-functional teams to build robust, explainable, and high-performance AI solutions in real-world production environments.

Key Responsibilities

• Design and implement end-to-end GenAI systems using LLMs (RAG, agents, tool use)
• Architect scalable and production-ready AI solutions for enterprise use cases
• Build and optimize retrieval pipelines using vector databases and hybrid search
• Develop prompting strategies, evaluation frameworks, and guardrails
• Integrate GenAI solutions with cloud platforms (AWS / Azure / GCP)
• Ensure system reliability, performance, and cost optimization
• Collaborate with stakeholders to translate business problems into AI solutions
• Mentor engineers and provide technical leadership across projects

Required Qualifications

• 8–13 years of experience in AI/ML or backend systems
• 2+ years of hands-on experience with LLMs and GenAI systems
• Strong experience with:RAG architectures
  Agent frameworks
  Prompt engineering & evaluation
  
• Proficiency in Python and SQL
• Experience with frameworks like LangChain, LangGraph, or similar
• Hands-on experience deploying solutions on AWS / Azure / GCP
• Strong system design and production deployment experience

Good to Have (Not Mandatory) – Knowledge Graphs

• Experience designing and working with Knowledge Graphs or semantic systems
• Familiarity with:Graph databases (Neo4j, Amazon Neptune, etc.)
  Ontologies, taxonomies, and semantic modeling
  Graph-based retrieval or Graph-RAG architectures
  
• Understanding of combining structured data (graphs) with LLMs for improved reasoning and explainability