AI Delivery Lead
Walker Smith
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Job summary
Tower in Auckland seeks an AI Delivery Lead to own end-to-end delivery across AI portfolio, turning roadmaps into delivery plans and milestones.
You will coordinate across engineering, data, architecture, risk and security to move initiatives from discovery to scale while embedding responsible AI controls.
Qualifications
- 8+ years of experience leading complex digital, data or AI delivery programs.
- Proven ability to translate product priorities into executable delivery plans.
- Strong understanding of generative AI, ML, and responsible AI practices.
- Excellent stakeholder management and cross-functional leadership.
Responsibilities
- Own intake, prioritisation and portfolio planning for AI use cases and infrastructure.
- Coordinate delivery across AI Engineering, Data, Architecture and Security teams.
- Lead discovery through production, ensuring clear hypotheses and go/no-go decisions.
- Maintain realistic delivery commitments and transparent progress reporting.
- Ensure responsible AI, privacy, security and governance considerations are embedded.
Skills
Job description
AI Delivery Lead Role
The AI Delivery Lead owns and drives the end-to-end delivery pipeline across Tower's AI portfolio, spanning AI architecture and technical foundations, reusable capabilities and priority operational use cases. The role converts agreed product priorities and the AI product roadmap into well-scoped delivery plans, sequencing, milestones and execution rhythms that move solutions from discovery and prototype through pilot, production, adoption and scale.
Working closely with the Head of AI & Insights, business leaders, the AI Centre of Excellence, Technology, Architecture, Data, Risk, Security, Privacy, Finance and delivery partners, this role provides a single point of delivery coordination across capacity, dependencies, risks, blockers, governance and trade-offs. The role creates momentum, removes barriers and ensures AI initiatives deliver measurable customer and business outcomes with responsible AI controls embedded throughout the lifecycle.
Own the intake process for operational AI use cases, technical foundations and enabling work across business-as-usual and transformation demand.
Partner with business stakeholders to understand the operational problem, target outcome, sponsor, benefits owner and success measures.
Assess, shape and challenge opportunities based on value, feasibility, data readiness, delivery complexity, adoption needs and risk.
Ensure proposed work is appropriately scoped, documented and ready for prioritisation.
Maintain a transparent view of incoming demand, delivery commitments, capacity and constraints.
Facilitate prioritisation discussions across operational AI use cases, architecture, platform enablement, regulatory commitments and technical debt, ensuring decisions are made by the appropriate product and business owners.
Translate agreed product priorities into an integrated delivery roadmap with clear outcomes, milestones, dependencies, governance activities and capacity needs.
Present delivery options, risks and trade-offs to decision-makers with practical recommendations.
Maintain a single view of AI delivery sequencing, investment, commitments and capacity against the product roadmap.
Ensure finite delivery capacity remains aligned to the highest-value and most strategically important product priorities.
Maintain a clear distinction between the product roadmap, owned by the Product Manager, and the delivery roadmap, owned by the AI Delivery Lead.
Coordinate delivery across AI Engineering, Data, Architecture, Technology, testing, security, risk, change and business teams.
Drive delivery cadence, maintain visibility of progress, dependencies, risks and blockers, and remove barriers that affect successful delivery.
Lead progression from discovery and rapid prototype through pilot, production, adoption and scaled operation.
Ensure experiments have explicit hypotheses, evaluation criteria and clear stop, pivot or scale decisions.
Ensure delivery commitments are realistic, transparent and actively managed.
Coordinate delivery of AI environments, integration patterns, data access, reusable services, model and agent operations, observability, security and release capabilities.
Work with architects and engineering leads to sequence foundational work against near-term use-case demand.
Ensure solution plans address production readiness, reliability, performance, consumption cost, identity and access, auditability, monitoring, fallback and support.
Promote modular and reusable patterns and capabilities that improve delivery speed and reduce unnecessary duplication and vendor lock-in.
Make technical dependencies and trade-offs understandable to business and governance stakeholders.
Act as the primary business-facing coordination point for AI delivery and build trusted relationships across business and technology teams.
Ensure sponsors and operational owners are actively engaged in process redesign, testing, adoption, change and benefits realisation.
Manage stakeholder expectations regarding delivery timing, dependencies, sequencing and resource constraints.
Facilitate delivery trade-off decisions where demand exceeds available capacity, escalating product priority choices to the Product Manager and accountable business owners.
Ensure delivered capabilities transition smoothly into operational ownership, support and continuous improvement.
Embed AI governance, privacy, security, legal, conduct, data and architecture requirements throughout delivery.
Ensure required evidence is maintained, including use-case documentation, risk assessments, evaluation results, decision logs, controls, test evidence and monitoring plans.
Coordinate readiness reviews and go or no-go decisions with appropriate human oversight, escalation, contestability and fallback arrangements.
Ensure residual risks are visible and accepted by the appropriate accountable owner.
Coordinate post-release monitoring, incident response and improvement using solution performance, user feedback, operational results and emerging risks.
Coordinate internal teams, strategic partners, vendors and surge resources against agreed priorities and outcomes.
Monitor delivery performance, quality, capacity, commercial outcomes and knowledge transfer.
Ensure partner activity contributes to reusable Tower capability rather than creating avoidable dependency.
Support effective planning, onboarding and utilisation of external resources.
Ensure each initiative has a clearly defined business outcome, baseline, success measure and benefits owner before delivery begins.
Partner with business sponsors and Finance to track delivery cost, AI consumption, adoption, performance and realised benefits.
Connect technical measures to outcomes such as cycle time, quality, cost-to-serve, customer experience, control effectiveness and capacity released.
Provide concise reporting on progress, spend, risks, dependencies, decisions, outcomes and realised value.
Challenge initiatives that are not evidencing sufficient value and recommend whether to stop, reshape, continue or scale.
Strong end-to-end programme, product or delivery leadership across complex technology-enabled transformation.
Practical understanding of generative AI, agentic AI, machine learning and automation delivery, including experimentation, evaluation, deployment, monitoring and continuous improvement.
Ability to connect business outcomes and value with technical scope, architecture, data, integration, security, change and operating-model requirements.
Strong demand management, prioritisation, roadmap planning, capacity planning, dependency management, financial management and executive reporting skills.
Experience applying agile, product and lean experimentation methods while retaining appropriate delivery control and governance.
Commercial acumen and confidence working with benefits cases, baselines, investment trade-offs, consumption economics, partner costs and ROI tracking.
Working knowledge of responsible AI, privacy, information security, model risk, human oversight and assurance in a regulated environment.
Sufficient technical fluency to challenge architects and engineers, understand delivery implications and identify when a prototype is not production-ready.
Exceptional facilitation, communication and stakeholder leadership skills, with the ability to create clarity and action across business and technical groups.
8+ years' experience leading complex digital, data, technology, product or transformation delivery across multiple concurrent workstreams.
Demonstrated experience taking emerging technology, data or AI solutions from concept or prototype into production and scaled operational use.
Proven record of coordinating multidisciplinary teams spanning engineering, architecture, data, risk, security, testing, change and business specialists.
Experience leading delivery across both technical foundations and business-facing use cases.
Experience managing strategic vendors, consultancies or system-integration partners, including delivery accountability, commercial outcomes and capability transfer.
Experience establishing demand and prioritisation processes, managing finite capacity and communicating delivery trade-offs to senior stakeholders.
Experience building business cases, defining measurable outcomes and partnering with Finance and business owners to track benefits realisation.
Experience in insurance, financial services or another regulated and operationally complex environment is preferred.
Relevant tertiary qualification or equivalent professional experience. Delivery, agile, product or programme certifications are useful, but demonstrated outcomes and judgement are more important.
Actively promote and role model risk and health & safety awareness, ensuring that colleagues use the relevant risk management tools and techniques.
Identify, report and elevate risks, health, safety and environmental hazards and understand the appropriate action to take.
Understand and meet legally binding health and safety regulations relevant to the workplace.
Complete health, safety and risk awareness training as required.
Align risk management considerations to the development and review of strategic objectives.
Tower prides itself on being a diverse and inclusive environment. We embrace and encourage our employees to bring their whole selves to work and to celebrate what makes every person unique. We are proud holders of the Rainbow Tick, which is an important statement for us.
We do what's right
Our people come first
Our customers are our compass
Progress boldly
To inspire, shape and protect the future for the good of our customers and co
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