Job
Description
Role Overview: As an AI Solution Architect and CoE Lead at CES, you will be playing a crucial role in leading the development, design, and implementation of artificial intelligence solutions within the organization. Your responsibilities will also include driving the strategy for AI excellence and best practices by establishing and overseeing the AI Centre of Excellence (CoE). This role requires you to focus on nurturing AI talent, promoting knowledge sharing, and continuously evolving AI practices across the organization. Key Responsibilities: - Design and Develop AI Solutions: Lead the end-to-end process of designing, developing, and deploying AI solutions tailored to business needs. - Technical Leadership: Provide technical guidance to cross-functional teams working on AI-related projects to ensure high standards in solution design, integration, and deployment. - Consulting and Advisory: Collaborate closely with stakeholders to identify business requirements and transform them into AI-powered solutions, including machine learning models, data pipelines, and AI-driven processes. - Platform Selection and Integration: Evaluate and choose appropriate AI tools, platforms, and technologies to meet business goals. Oversee integration with existing systems, ensuring scalability and efficiency. - Optimization and Innovation: Continuously monitor, optimize, and evolve AI solutions to keep the organization at the forefront of AI advancements. Centre of Excellence (CoE) Management: - CoE Strategy Development: Develop and implement a strategy for the AI Centre of Excellence, ensuring alignment with business objectives and AI best practices. - Knowledge Sharing and Governance: Establish frameworks for knowledge sharing, training, and governance to ensure consistent and scalable AI practices across the organization. - Innovation Culture: Foster a culture of innovation and experimentation, encouraging cross-functional collaboration and new AI research and application. - Talent Development: Lead efforts to upskill internal teams through training sessions, workshops, and seminars focused on the latest AI technologies and methodologies. - Standardization and Best Practices: Define AI-related standards, processes, and best practices across the organization to maintain quality and consistency. Stakeholder Engagement: - Cross-Functional Collaboration: Collaborate with business leaders, data scientists, IT teams, and product managers to deliver effective AI solutions. - Client-facing Engagement: Engage with clients to understand their needs, showcase AI capabilities, and offer thought leadership on how AI can address their challenges. - Executive Reporting: Regularly report to senior leadership on the progress of AI initiatives, highlighting key milestones, risks, and opportunities. Research and Development: - Emerging Technologies: Stay updated on the latest AI technologies, evaluate their potential impact on business processes, and lead the development of PoCs and pilot projects. - AI Governance and Compliance: Ensure the responsible and ethical use of AI, considering fairness, transparency, privacy, and security issues. Maintain compliance with AI-related regulations and standards. Qualifications: Education: - Bachelors or Masters degree in Computer Science, Engineering, Data Science, AI, or a related field. A Ph.D. in AI or related fields is a plus. Experience: - 11+ years of experience in AI, machine learning, or data science, with a proven track record of delivering AI solutions. - 7+ years of experience in a leadership or architecture role, ideally with some experience in leading a Centre of Excellence. - Hands-on experience with AI frameworks such as TensorFlow, PyTorch, Scikit-learn, and cloud platforms like AWS, Azure, or Google Cloud. - Experience in multiple industries is advantageous. Skills: - AI/ML Expertise: Strong understanding of machine learning algorithms, deep learning, natural language processing, computer vision, and data-driven problem-solving techniques. - Architecture Skills: Proven ability to design and architect scalable, reliable, and high-performance AI solutions. - Leadership and Communication: Excellent leadership skills with the ability to influence and collaborate with cross-functional teams. Strong presentation and communication skills. - Project Management: Experience managing large, complex projects with diverse teams and tight deadlines. - Governance and Best Practices: Deep understanding of AI governance frameworks, industry standards, and ethical guidelines. Certifications (Optional): - Certified AI Professional. - Certified Solutions Architect. Preferred Traits: - Visionary Thinker: Ability to foresee AI trends and strategically leverage them for business growth. - Problem Solver: Strong analytical skills and innovative mindset to solve complex business problems using AI. - Mentor: Passion for mentoring and developing the next generation of AI talent.,
