AI Engineering Lead

AI Engineering Lead

Location: India

Employment Type: Full-Time

What We’re Looking For

AI Engineering Lead

Required skills:

• 12+ years of professional experience as a software engineer and building applications/systems.
• 2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques, particularly multi-agent systems.
• Expert proficiency in programming skills in Python, Langgraph, and SQL is a must.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services.
• Expert proficiency in using AI tools like Claude Code, Codex, cursor, windsurf, and the like.
• Expert proficiency in AI observability & evaluation tools like Langsmith, Langfuse, or similar.
• Good proficiency in using various cloud services from Azure, GCP, or AWS for building GenAI applications.
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs.

Roles & Responsibilities:

Solutioning & Lead

• Build the technical roadmap given a business requirement and own the delivery of the same.
• Lead the engineering team toward a technical roadmap and ensure the timely execution of the roadmap to achieve customer satisfaction.
• Design robust multi-agent architectures, including supervisor-router patterns with dynamic sub-agent routing and stopping conditions.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

Hands-on skills

• Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent-based architectures.
• Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs.
• Codebase ownership: Build & maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.

Communication & Cross-functional collaboration

• Actively follows the frontier and has differentiated, up-to-date views on model releases, agentic architectures, evaluation methods, tool-use and computer-use patterns, multimodal capability, reasoning/test-time compute trends, and the serious open questions in the field.
• Produce a structured, high-signal answer to an open-ended technical or strategic question — while modulating depth for a non-engineering executive audience.
• Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.

About Turing

Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. They connect elite AI professionals with frontier model training projects, offering competitive compensation for domain expertise across coding, STEM, creative writing, and more.

How To Apply

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