Data Science & AI Platform Team Lead

Proudly founded in Australia, we are a global energy company providing reliable and affordable energy to help people lead better lives. Woodside Global Solutions in Bengaluru brings together talent, digital expertise and operational excellence to support Woodside's global operations.

Woodside Global Solutions in Bengaluru is being built as a hub of excellence, to drive innovation and global collaboration. We are looking for talented professionals who are eager to make a global impact, helping to shape the future of Woodside together.

The Data Science & AI Platform Team Lead is responsible for leading a team of AI Developers dedicated to building and enhancing platform capabilities that enable scalable, secure, and reliable AI delivery. This role ensures all work aligns with the AI practices, standards, and governance set by the AI Lead in Australia and consults closely with existing platform practices. Acting as the focal point for platform engineering in India, the AI Platform Lead drives technical excellence, fosters collaboration, and accelerates the development of reusable AI platform components that support enterprise AI agents and applications.

Safety & Operational Excellence

• Champion a strong safety culture and support zero-incident outcomes in AI platform and Data Science Platform operations.
• Ensure secure, compliant, and auditable platform practices and deployment processes to reduce operational risk.

Leadership

• Lead and mentor a team of AI Developers focused on platform capabilities.
• Lead and mentor a team of Data Science Platform Developers focused on platform capabilities.
• Drive self-leadership and ongoing capability development within the platform standards and practices.
• Foster a culture of engineering excellence, safe experimentation, and continuous improvement.
• Act as the primary liaison between India-based platform team and the Head of AI, ensuring alignment with global standards and practices.
• Advocate for modern AI engineering practices, governance, and responsible AI adoption.

Work Processes & Systems

• Ensure compliance with Woodside Management System (WMS) requirements.
• Implement and maintain best practices, standards, and reusable patterns for Data Science platform development and operations.
• Implement and maintain best practices, standards, and reusable patterns for AI platform development and operations.
• Oversee platform reliability, performance, observability, and lifecycle management.

Technical

• Define and evolve platform capabilities in consultation with global platform architecture and standards.
• Lead development and implementation of reusable frameworks, APIs, and services that accelerate AI delivery.
• Ensure platform components are secure, maintainable, and aligned with enterprise architecture and Data Science strategy.
• Ensure platform components are secure, maintainable, and aligned with enterprise architecture and AI strategy.
• Translate technical requirements into platform features that enable rapid deployment of Data Science and AI solutions.
• Stay current with emerging Data Science and AI technologies, especially Generative AI, and integrate relevant advancements into platform capabilities.

Key Accountabilities

• Delivery of AI platform capabilities that enable measurable business value.
• High platform reliability, availability, and performance.
• Effective collaboration with global platform teams, AI and Data Science Tech Chapter Lead, and other stakeholders.
• Adoption of platform capabilities by AI development teams and Data Scientists.
• Enabling faster and safer delivery of AI agents and solutions.
• Enabling faster and safer delivery of Data Science platform solution and applications.

Technical Skills / Experience:

• Bachelor’s degree in Computer Science or Software Engineering, or related field.
• 11 to 16 years of experience in platform engineering or enterprise architecture, with at least 3 years in AI/ML or Generative AI environments.
• Strong expertise in Generative AI frameworks (OpenAI or similar) and orchestration tools.
• Experience with cloud platforms (AWS, Azure) and building solutions within those environments, containerisation (Docker, Kubernetes), and CI/CD pipelines.
• Knowledge of AI and DS platform components: model hosting, MLOPS, inference APIs, vector databases, prompt orchestration frameworks.
• Proven ability to lead technical teams and deliver reusable, scalable platform solutions.
• Familiarity with Responsible AI principles and governance frameworks.
• Excellent leadership, stakeholder engagement, and communication skills.