AI COE Lead (Artificial Intelligence - COE Lead)

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About the Client:

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A leading global IT services and technology distribution company.

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Role : Artificial Intelligence - Centre of Excellence Lead (AI COE Lead)

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Location : Chennai

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Role Summary:

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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 \n

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• 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.
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• 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.
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• 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.
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2. MLOps & Production Scaling \n

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• 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.
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• Performance Engineering: Optimize inference pipelines and AI model efficiency using frameworks like ONNX and DeepSpeed to ensure low-latency, high-throughput performance in production.
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• System Integration: Ensure secure and resilient integration of AI services and APIs with core business applications and existing infrastructure.
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3. Team Leadership & Business Impact \n

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• 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.
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• Business Automation: Identify and execute AI-powered automation initiatives that result in measurable improvements in operational efficiency, workflow simplification, and enhanced business decision-making.
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• Ethical AI & Compliance: Define and uphold standards for AI Ethics, bias mitigation , and regulatory compliance in all AI solution designs and deployments.
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Required Skills & Qualifications Educational Background \n

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• Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field.
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Essential Technical Expertise \n

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• Extensive experience in leading and shipping enterprise-scale AI/ML products.
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• Deep, demonstrable expertise in Generative AI, LLMs, and RAG systems .
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• Hands-on, production-level experience with MLOps and LLMOps practices (e.g., orchestration, CI/CD for ML, monitoring).
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• Expert proficiency in major AI/ML frameworks: PyTorch, TensorFlow , and optimization frameworks like ONNX or DeepSpeed .
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• Proven experience in NLP, Computer Vision, or time-series AI solutions .
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• Strong background in cloud-native AI development and services (e.g., AWS SageMaker, Azure ML, Google AI Platform) is a significant advantage.
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Leadership & Soft Skills \n

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• Demonstrated ability to communicate complex AI concepts and strategies to both technical teams and non-technical Senior Leadership/Stakeholders .
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• Proven track record of driving tangible business impact through deployed AI solutions.
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• Exceptional team leadership, mentorship, and project management capabilities.
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