Saaki Argus and Averil Consulting logo

AI COE Lead (Artificial Intelligence - COE Lead)

0 years

0 Lacs

chennai tamil nadu india

Posted:1 day ago| Platform: Linkedin logo

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Skills Required

ai technology deployment leadership ml pipeline architecture drive strategy graphs retrieval development training tuning data design governance scaling monitoring versioning inference model efficiency latency integration automation workflow ethics compliance shipping orchestration pytorch optimization onnx vision aws sagemaker azure strategies management

Work Mode

On-site

Job Type

Full Time

Job Description

About the Client:


A leading global IT services and technology distribution company.


Role


Location


Role Summary:


AI Lead

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.

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