Principal GenAI Engineer MultiAgent-Hybrid -Marathalli

About the role

Turing is hiring a Principal GenAI Engineer to architect, build, and deliver production-grade AI solutions for Fortune 500 enterprise customers.

This is a hands-on technical leadership role combining Python engineering, GenAI architecture, and direct client collaboration. You will own solutions from business requirements and technical design through implementation, production deployment, and optimization, while guiding a cross-functional engineering team.

Required skills

• 10+ years of professional, hands-on engineering experience, including 4+ years building and deploying AI/ML systems.
• 1+ year of hands-on experience developing and deploying production GenAI applications using LLMs, RAG, and agentic architectures.
• Demonstrated experience building multi-agent systems, including agent orchestration, tool calling, state management, and failure handling.
• Expert proficiency in Python and strong SQL skills, with hands-on experience using LangGraph and LangChain.
• Experience architecting scalable backend services, APIs, and enterprise GenAI applications.
• Proficiency in deploying and operating applications on at least one cloud platform: Azure, GCP, or AWS.
• Experience owning technical roadmaps, leading architecture decisions, reviewing code, and mentoring engineers.
• Excellent communication skills, with the ability to translate business requirements into technical solutions and explain architectural trade-offs to clients and business stakeholders.

Roles & responsibilities

• Own architecture and delivery: Translate customer requirements into solution designs and technical roadmaps, taking ownership through production rollout.
• Build agentic applications: Design and implement multi-agent workflows, tool integrations, and LLM-powered applications.
• Develop production RAG systems: Own document ingestion, retrieval, context management, and evaluation to improve answer quality.
• Remain hands-on: Write and review Python code, build reusable components, and resolve complex engineering challenges.
• Ensure production quality: Establish evaluation, guardrails, observability, and monitoring; optimize reliability, latency, scalability, and cost.
• Own cloud deployment: Guide deployment on Azure, GCP, or AWS, including integration with enterprise systems and CI/CD processes.
• Partner with customers: Work closely with product owners, business SMEs, and engineering teams to clarify requirements, communicate progress, and deliver business outcomes.
• Provide technical leadership: Guide execution, mentor engineers, and establish engineering standards across the project.
• Evaluate emerging approaches: Assess models, frameworks, and techniques, applying prompt engineering, retrieval improvements, or fine-tuning where appropriate.