Practice Lead - AI & Data Products

A Snapshot

The Practice Lead – AI & Data Products is a senior leadership position responsible for shaping, delivering, and scaling Airtrunk’s AI and data product ecosystem. Reporting to the Senior Director – AI, Automation & Data Insights, this role blends product leadership, platform strategy, and applied AI and data innovation, ensuring that the business maximises the value of its data assets and accelerates adoption of AI-driven capabilities across the enterprise. You will lead a small, high-performing team of technical product managers, and analytics / AI engineers to design, build, and scale reusable AI and data products. As a core member of the AI and Data leadership team, you will help define the vision, standards, and operating model that transform AI and data into enterprise-grade products used by every business unit. 

Your Day to Day 

Strategic Leadership

• Partner with the Senior Director – AI, Automation & Data Insight to define and execute the multi-year AI and Data strategy aligned to business priorities.
• Translate AI and data platform capabilities into tangible business products and outcomes.
• Drive strong mutually beneficial partnerships with external vendors across the AI and data landscape.
• Drive the adoption of an AI and data product mindset across the organisation, establishing best practices, governance patterns, and value measurement frameworks.
• Contribute to enterprise-level planning, budgeting, and capability roadmaps for AI, automation and data.

Technical Product Ownership & Delivery

• Lead the definition and delivery of reusable AI and data products that integrate data pipelines, analytics models, and machine learning components into deployable solutions.
• Prioritise and manage the product backlog in partnership with business and technical stakeholders.
• Champion AI and data product lifecycle management — from discovery, design, experimentation, and delivery through to monitoring, adoption, and ROI measurement.
• Establish product success metrics, SLAs, and clear value realisation tracking.

People Leadership

• Build, coach, and empower a team of technical product managers, analytics engineers, and AI engineers.
• Foster a high-performance, high-trust culture that balances innovation with reliability and governance.
• Provide mentorship and career development pathways across the AI, automation and Data Insights team.

Technology & Architecture

• Collaborate with the Data Platform and Engineering team to ensure the underlying AI, ML and data platforms support scalable and secure product delivery.
• Oversee alignment of data product contracts, APIs, and governance patterns to enterprise standards (metadata, lineage, quality, and privacy).
• Evaluate emerging AI technologies (agentic automation, LLMs, integration patterns like MCP) and identify opportunities to embed them in the platform ecosystem.

Business Partnership

• Serve as a trusted advisor to business executives, helping them articulate problems that can be solved through AI and data products.
• Drive cross-functional collaboration with stakeholders across every business unit to accelerate adoption.
• Communicate complex technical concepts to non-technical stakeholders with clarity and confidence.

Requirements

• 10+ years of experience across data, analytics, or AI disciplines, with at least 3+ years in a leadership or product ownership role.
• Proven success leading cross-functional data or AI product teams in complex, cloud-based environments.
• Strong understanding of modern data platform architectures (Snowflake, Databricks, Kafka, dbt, etc.) and MLOps / AI delivery frameworks.
• Demonstrated experience deploying agentic automation frameworks or generative AI solutions with measurable impact.
• Exceptional stakeholder management and communication skills; comfortable operating at executive level.
• Experience scaling AI observability, data governance, product management, and agile delivery within data/AI contexts.
• Experience in high-growth or digital transformation environments (tech, fintech, infrastructure, or SaaS).
• Knowledge of responsible AI frameworks, policies and standards.
• Strategic thinker who balances innovation with operational excellence.
• Product-led mindset with a bias toward simplicity, reusability, and measurable value.
• Natural coach and culture builder - elevates talent and promotes continuous learning.
• Pragmatic and execution-focused, able to deliver progress in ambiguity.
• Passionate about building a sustainable, ethical, and high-impact AI and data ecosystem.