AI Solution Architect

Key Responsibilities

• Strategic Leadership

  • Define and lead the enterprise-wide AI strategy aligned with business goals.
  • Identify opportunities where AI can deliver competitive advantages, operational efficiencies, or new revenue streams.
  • Collaborate with executive leadership to prioritize and fund AI initiatives.

• Team & Capability Building

  • Build, mentor, and manage cross-functional AI/ML teams (Data Scientists, ML Engineers, AI Researchers).
  • Foster a culture of innovation, experimentation, and continuous learning.

• AI Solution Delivery

  • Oversee the development and deployment of AI/ML models, from proof-of-concept to production.
  • Ensure scalability, performance, and ethical standards in all AI deployments.
  • Partner with Product, Engineering, and Data teams to integrate AI into products, platforms, or internal tools.

• Governance & Risk Management

  • Define policies for responsible and ethical AI use.
  • Ensure compliance with data privacy, AI regulations, and industry standards.
  • Implement robust model governance, monitoring, and explainability frameworks.

• Stakeholder Management

  • Act as the AI subject matter expert and evangelist for internal and external stakeholders.
  • Present insights, strategies, and outcomes to C-level executives, clients, and partners.

• Innovation & Research

  • Stay abreast of emerging AI trends, technologies, and academic research.
  • Evaluate and incorporate cutting-edge techniques (e.g., generative AI, LLMs, reinforcement learning) where applicable.

Qualifications

• Master s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
• 18+ years of IT experience.
• 8-10 years of experience in data science, machine learning, or AI, with at least 5 years in leadership roles.
• Strong hands-on expertise in ML frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, Scala), and cloud platforms (AWS, Azure, GCP).
• Proven track record of delivering large-scale AI/ML initiatives in a business context.
• Deep understanding of AI architecture, MLOps, model lifecycle, and deployment at scale.
• Excellent communication and stakeholder management skills.

• Experience in BFS / Insurance / Healthcare / T&H.
• Familiarity with generative AI, LLMs (e.g., GPT, BERT), and NLP technologies.
• Prior experience with AI governance and responsible AI frameworks.