Solution Architect - AI

About the Client:

Our client has 26+ years of experience in delivering Software Product Development, Quality Engineering, and Digital Transformation Consulting Services to Global SMEs & Large Enterprises. They has been delivering services to some of the leading Fortune 500 Companies including Automotive, AdTech, Bio Science, EdTech, FinTech, Manufacturing, Online Retailers, and Investment Banks.

Responsibilities:

1. Al Solution Architecture:

· Design and Develop Al Solutions: Lead the end-to-end process of designing, developing, and deploying Al solutions tailored to business needs.

• Technical Leadership: Provide technical leadership to cross-functional teams working on Al-related

projects, ensuring high standards in solution design, integration, and deployment.

• Consulting and Advisory: Work closely with stakeholders to identify business requirements and translate them into Al-powered solutions, including machine learning models, data pipelines, and Al- driven processes.

• Platform Selection and Integration: Evaluate and select appropriate Al 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 Al solutions, keeping the organization at the forefront of Al advancements.

2. Centre of Excellence (COE) Management:

• COE Strategy Development: Develop and implement a strategy for the Al Centre of Excellence, ensuring alignment with business objectives and Al best practices.

· Knowledge Sharing and Governance: Establish frameworks for knowledge sharing, training, and governance, ensuring that Al practices are consistent and scalable across the organization.

• Innovation Culture: Foster a culture of innovation and experimentation, encouraging cross- functional collaboration and new Al research and application.

• Talent Development: Lead efforts to upskill internal teams by organizing training sessions,

workshops, and seminars focused on the latest Al technologies and methodologies.

• Standardization and Best Practices: Define Al-related standards, processes, and best practices across the organization. Ensure all teams adhere to these guidelines to maintain quality and consistency.

3. Stakeholder Engagement:

• Cross-Functional Collaboration: Collaborate with business leaders, data scientists, IT teams, and product managers to deliver effective Al solutions.

Client-facing Engagement: Engage with clients to understand their needs, demonstrate Al

capabilities, and provide thought leadership on how Al can address their challenges.

• Executive Reporting: Regularly report to senior leadership on the progress of Al initiatives, highlighting key milestones, risks, and opportunities.

4. Research and Development:

Emerging Technologies: Stay updated on the latest developments in Al technologies, including deep learning, reinforcement learning, natural language processing (NLP), and computer vision, and evaluate their potential impact on business processes.

• Proof of Concept (POC): Lead the development of PoCs and pilot projects to test Al ideas and validate their feasibility before broader implementation.

5. Al Governance and Compliance:

• Ethical Al: Ensure the responsible and ethical use of Al, taking into consideration issues related to fairness, transparency, privacy, and security.

Compliance: Maintain awareness of Al-related regulations and ensure the organization's solutions adhere to legal, ethical, and industry standards.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Al, or a related field. A Ph.D. in Al or related fields is a plus.

Experience:

• 11+ years of experience in Al, machine learning, or data science, with a proven track record of delivering Al solutions.

• 7+ years of experience in a leadership or architecture role, ideally with some experience in leading a Centre of Excellence or a similar initiative.

• Hands-on experience with Al frameworks such as TensorFlow, PyTorch, Scikit-learn, and cloud platforms like AWS, Azure, or Google Cloud.

• Experience in multiple industries is advantageous (e.g., healthcare, finance, retail).

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 Al solutions.

• Leadership and Communication: Excellent leadership skills with the ability to influence and

collaborate with cross-functional teams. Strong presentation and communication skills for engaging stakeholders at all levels.

• Project Management: Experience managing large, complex projects with diverse teams and tight deadlines.

· Governance and Best Practices: Deep understanding of Al governance frameworks, industry standards, and ethical guidelines.

Certifications (Optional):

• Certified Al Professional (e.g., Microsoft Certified: Azure Al Engineer, AWS Certified Machine Learning).

• Certified Solutions Architect (e.g., AWS Solutions Architect, Google Professional Cloud Architect). Preferred Traits:

· Visionary Thinker: Ability to foresee Al trends and leverage them strategically for business growth.

• Problem Solver: Strong analytical skills and an innovative mindset to solve complex business problems using Al.

• Mentor: Passion for mentoring and developing the next generation of Al talent.