AI COE Lead (Artificial Intelligence - COE Lead)

Job Description

About the Client: A leading global IT services and technology distribution company. Role : Artificial Intelligence - Centre of Excellence Lead (AI COE Lead) Location : Chennai Role Summary: The AI Lead will champion the enterprise-wide adoption and strategic deployment of Artificial Intelligence, with a strong emphasis on Generative AI and scalable LLMOps . This is a critical leadership role responsible for translating complex business challenges into high-impact, production-ready AI/ML solutions. You will be instrumental in building a robust AI innovation pipeline, leading a high-performing technical team, and defining the architecture required for secure, ethical, and performant AI systems that drive significant business transformation and efficiency. Responsibilities & Deliverables 1. Generative AI Strategy & Architecture ?? Establish and Own the Generative AI Stack: Architect and implement a complete Generative AI ecosystem, encompassing fine-tuned Large Language Models (LLMs), domain-specific knowledge graphs, and Retrieval-Augmented Generation (RAG) systems. LLM Development and Optimization: Lead the development, training, and fine-tuning of proprietary LLMs using advanced techniques to ensure relevance and accuracy for business operations. Data Foundation: Design and enforce an enterprise-level data architecture and data governance strategy (clean, complete, and accessible data) essential for fueling advanced AI/ML and analytics. 2. MLOps & Production Scaling ?? Scalable AI Infrastructure: Direct the implementation of LLMOps and robust MLOps practices to achieve seamless, automated deployment, monitoring, and versioning of all AI/ML models across enterprise systems. Performance Engineering: Optimize inference pipelines and AI model efficiency using frameworks like ONNX and DeepSpeed to ensure low-latency, high-throughput performance in production. System Integration: Ensure secure and resilient integration of AI services and APIs with core business applications and existing infrastructure. 3. Team Leadership & Business Impact ?? Technical Leadership: Recruit, mentor, and lead a diverse team of Data Scientists, AI Engineers, and MLOps Professionals , fostering a culture of technical excellence, accountability, and continuous learning. Business Automation: Identify and execute AI-powered automation initiatives that result in measurable improvements in operational efficiency, workflow simplification, and enhanced business decision-making. Ethical AI & Compliance: Define and uphold standards for AI Ethics, bias mitigation , and regulatory compliance in all AI solution designs and deployments. Required Skills & Qualifications Educational Background Bachelor?s or Master?s degree in Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field. Essential Technical Expertise Extensive experience in leading and shipping enterprise-scale AI/ML products. Deep, demonstrable expertise in Generative AI, LLMs, and RAG systems . Hands-on, production-level experience with MLOps and LLMOps practices (e.g., orchestration, CI/CD for ML, monitoring). Expert proficiency in major AI/ML frameworks: PyTorch, TensorFlow , and optimization frameworks like ONNX or DeepSpeed . Proven experience in NLP, Computer Vision, or time-series AI solutions . Strong background in cloud-native AI development and services (e.g., AWS SageMaker, Azure ML, Google AI Platform) is a significant advantage. Leadership & Soft Skills Demonstrated ability to communicate complex AI concepts and strategies to both technical teams and non-technical Senior Leadership/Stakeholders . Proven track record of driving tangible business impact through deployed AI solutions. Exceptional team leadership, mentorship, and project management capabilities.