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AI COE Lead (Artificial Intelligence - COE Lead)

Saaki Argus & Averil Consulting
Chennai, Tamil Nadu

Quick apply

Job details

Qualifications

TensorFlow
CI/CD
Image processing
Azure
Law
Computer Science
Computer vision
Enterprise Software
Master's degree
AWS
Project management
Bachelor's degree
Continuous integration
Natural language processing
APIs
Data science
AI
Leadership
Graph databases
Data Science

Full 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

Bachelors or Masters 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.

Quick apply

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Responsibilities & Deliverables

1. Generative AI Strategy & Architecture

2. MLOps & Production Scaling

3. Team Leadership & Business Impact

Required Skills & Qualifications

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Essential Technical Expertise

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