Solution Architect - AI (Remote)

About the Client:

The company 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.

Job Overview:

The Al Solution Architect and COE Lead will play a pivotal role in leading the design, development, and implementation of artificial intelligence solutions within the organization. This position will also be responsible for driving the strategy for Al excellence and best practices by establishing and overseeing the Al Centre of Excellence (COE). The COE will focus on nurturing Al talent, fostering
knowledge sharing, and continuously evolving Al practices across the organization

Location: Chennai, Onsite

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.

Key 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.

#J-18808-Ljbffr