The AI Delivery Lead is responsible for orchestrating the end-to-end delivery of our multi-component AI platform, ensuring all workstreams; engineering, data, product, design, QA, and vendor partners move in lockstep. Working in close collaboration with a Delivery Manager who owns day-to-day technical execution, the Delivery Lead focuses on program-level orchestration, stakeholder navigation, and delivery governance across all workstreams. This role ensures that timelines, requirements, dependencies, and quality standards are consistently met across a complex ecosystem involving agents, MCPs, media processing, and data-driven functionality. You will be the connective tissue of the program, creating structure, removing blockers, and ensuring clarity for teams building a world-class AI toolset. Success in this role requires strong technical delivery experience, exceptional communication skills, and the ability to manage multi-team execution in a fast-moving environment. Responsibilities Program & Project Leadership • Own the integrated program view across all workstreams, maintaining a master delivery plan that reflects dependencies, milestones, risks, and resource allocation at the program level, in close coordination with the Delivery Manager who owns sprint-level execution • Ensure the delivery narrative remains coherent and visible to leadership at all times, translating ground-level progress into clear program-level status, decisions needed, and forward-looking risk signals Cross-Functional Coordination • Manage alignment across engineering, product, design, QA, data/ML teams, and third-party partners at the program level, working in tandem with the Delivery Manager who holds the day-to-day operational relationship with the development team • Support main stakeholders in navigating organizational and political complexity across business units with competing priorities, maintaining a clear and unified delivery direction at the executive level. • Identify, communicate, and escalate (technical, operational, resourcing, or vendor-related) with clear context and recommendations for decision-makers. • Ensure all teams have the access, documentation, assets, and clarity needed to deliver their work, removing structural blockers that fall outside the Delivery Manager's execution perimeter. Quality, Documentation & Testing • Establish and govern documentation frameworks across technical architecture, workflows, releases, and change management, ensuring consistency and traceability at the program level • Ensure the platform is fully validated before major milestones and releases, with clear stakeholder sign-off. Stakeholder Management • Serve as the primary delivery interface with senior leadership and executive stakeholders, providing clear, concise, and timely updates on program progress, risks, blockers, burn rates, team health and priorities. • Work closely with the Product Owner to ensure that scope, and sequencing remain aligned to business goals, and that trade-off decisions are surfaced and resolved at the right level • Manage expectations across internal and external teams, ensuring transparency and predictability. • Manage governance and decision-making touch points, escalating concerns early with clear context and recommendations, and ensuring that all relevant stakeholders remain informed and aligned. Operational Readiness & Rollout • Coordinate go-to-market and operational handoff activities, including training, knowledge transfer, and support models. • Champion continuous improvement of delivery practices as the product scales. • Ensure post-launch monitoring, incident management processes, and continuous improvement rhythms are in place. • Support recruiting and selection of delivery and operations talent to strengthen execution capability as the organization grows. AI Delivery & Governance • Ensure that responsible AI practices are embedded into the delivery process (model evaluation, bias-testing, data/security compliance, and HITL processes) • Partner with legal/compliance on data governance, privacy across all applicable regulatory obligations for data handling, storage and AI outputs. • Oversee model deployment workflows in close coordination with engineering for versioning, monitoring, drift detection and rollback processes. Qualifications • 7-10+ years of experience in digital delivery, technical program management, or a similar role. • Proven experience managing large-scale, multi-stream technical delivery programs (Agentic/AI/ML, data, or platform builds preferred). • Agile certified (an asset) • Deep understanding of Agile frameworks (Scrum or Kanban) including backlog prioritization, sprint planning, and close collaboration with a cross-functional development team • Strong understanding software development lifecycles, agile methodologies, and release management. • Strong understanding of AI product lifecycles • Experience partnering with legal/compliance and security teams. • Exceptional communication, facilitation, and stakeholder management skills. • Experience with tools such as Jira, Confluence, Miro, Figma and cloud-based monitoring or delivery platforms. • Ability to simplify complexity and drive structure in fast-moving, ambiguous environments. • You can tackle anything thrown your way. You are excited by figuring out things they've never done before. You do not have "that's not my job" in their vocabulary. Additional Information What Success Looks Like (First 6 Months) • A clear, predictable delivery rhythm established across all internal and external workstreams. • All AI components integrated into a master plan with documented dependencies and risk mitigations. • The first major release of the AI platform delivered with quality, transparency, and cross-functional alignment. • Reliable reporting, documentation, and communication practices implemented. • Strong trust and collaboration established with Product, Technology, and executive stakeholders. Salary Transparency matters to us. The salary range for this position is $150,000 to $160,000 per year. Actual compensation within this range will be based on a variety of factors, including relevant experience, knowledge, skills, and applicable certifications. This range reflects what we reasonably expect to offer based on current market data. AI Use We use artificial intelligence tools to support parts of our hiring process, such as reviewing applications or analysing resumes. These tools assist our recruitment team but never replace human decision-making. We believe in a human-first approach, where your experience and potential are recognised by people.