AI Delivery Manager [CCP for ICT Professionals (Strategy and Governance)]

DAYOS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Dayos is building an AI-first platform-focused delivery team in Singapore. We are seeking an AI Delivery Manager to lead programs that integrate Product, Engineering, and GTM, delivering measurable outcomes and successful go-lives.

You will formulate Agile frameworks for AI delivery, coach teams on planning and collaboration, and adapt plans as client requirements evolve. This role emphasizes stakeholder alignment, risk management, and ongoing process improvement.

Responsibilities

• Formulate and embed Agile coaching frameworks tailored to AI delivery projects, guiding internal teams in adopting Agile principles and practices.
• Provide hands-on coaching to strengthen sprint planning, backlog management, and cross-functional collaboration, fostering continuous improvement across enterprise AI deployments.
• Adapt delivery plans to customer business changes and stay responsive to shifts in leadership, reprioritization, or resource constraints.
• Understand customer business landscapes during onboarding to shape realistic delivery plans and stakeholder communications.
• Spot new opportunities during delivery to identify high-impact automation or AI tooling.
• Contribute to customer success storytelling by gathering measurable outcomes and creating internal references with Marketing.
• Translate business requirements into onboarding plans with measurable KPIs.
• Align internal teams and external stakeholders around a single delivery plan with documented milestones.
• Bridge sales intent and engineering output by ensuring delivery aligns to requirements.
• Track IT risks and unblock delivery issues, coordinating with Sales or Engineering to keep timelines on track.
• Manage customer transitions through change with clear communication and user education.
• Implement data analytics processes to capture delivery performance and AI adoption rates across enterprise SaaS integrations.
• Transform data insights into dashboards and visualisations using Power BI and Notion.
• Monitor ERP/HCM AI tooling developments and apply user-centered onboarding and adoption strategies.

Job description

About Dayos

Dayos is the AI-first version of the systems integrators and application management firms that have supported enterprise ERPs for decades. We're building this company in Singapore, for the long term.

Hero, our platform, doesn't just watch your systems. It logs in, does the work, and validates the output inside Oracle, Workday and SAP. At a Singapore enterprise, Hero closed 9 of 10 support tickets that had been open for an average of three weeks, taking roughly 10 minutes per request.

Every company in the world runs Oracle, Workday or SAP, and many run more than one. Yet no school teaches students how to implement and manage them, and fewer people do this work every year. That gap is what we're built to close.

Enterprises spend billions every year supporting these systems, and much of that work is still manual. Three years building Hero. Enterprise customers already in production. Now we're closing our seed round and building the Singapore go-to-market team from the ground up.

Why Join Us?

We're creating a new category of delivery leadership-one that blends customer onboarding, agile execution, and success storytelling in a single role. If you want to lead programs that actually deliver results (not get handed off between departments), this is your opportunity.

What You Will Do

As an AI Delivery Manager, you will:

• Formulate and embed Agile coaching frameworks tailored to AI delivery projects, guiding internal teams (Product, Engineering, Delivery) in adopting Agile principles and practices.
• Provide hands-on coaching to strengthen sprint planning, backlog management, and cross-functional collaboration, fostering a culture of continuous improvement and adaptability across enterprise AI solution deployments.
• Adapt delivery plans to customer business changes - Stay responsive when customer priorities shift due to leadership changes, project reprioritization, or resource constraints.
• Understand the customer's business landscape - During onboarding, identify industry-specific constraints or regulations (e.g., data residency in financial services or compliance in public sector) that could impact delivery. Use this knowledge to shape realistic delivery plans and stakeholder communication.
• Spot new opportunities during delivery - Identify high-impact areas for additional automation or AI tooling as project unfold.
• Contribute to customer success storytelling - After successful go-lives, gather measurable outcomes and turn them into case studies or internal references, in collaboration with Marketing.
• Translate business requirements into structured onboarding plans with measurable KPIs.
• Align internal teams (Product, Engineering, GTM) and external stakeholders around a single delivery plan with clearly documented milestones.
• Bridge sales intent and engineering output by ensuring all delivery aligns to customer-specified requirements.
• Track IT risks and unblock delivery issues - Proactively flag potential blockers, document them, and work with Sales or Engineering to keep timelines on track.
• Manage customer transitions through change - Guide stakeholders through delivery phases with clear communication, documentation, and user education.
• Implement data analytics processes to capture and interpret delivery performance, AI adoption rates, and customer usage trends across enterprise SaaS integrations.
• Transform data insights into dynamic dashboards and interactive visualisations using tools such as Power BI and Notion.
• Track ERP/HCM AI tooling developments - Stay current on emerging enterprise AI capabilities (e.g., automated reconciliations, intelligent routing, predictive analytics) and apply user-centered thinking to design onboarding journeys and post-launch adoption strategies that improve customer enablement and long-term success.
• Support customer and team readiness through structured learning moments - Share onboarding insights, update delivery playbooks, and mentor new team members on our implementation lifecycle.
• Collaborates with internal teams to anticipate resourcing needs for upcoming customer programs.
• Builds partnerships and client rapport during onboarding and ongoing program collaboration.
• Evaluate organisational structures, resource availability, and decision‑making processes to identify factors that may impact delivery performance and use these insights to adjust stakeholder engagement approaches, documentation cadence and delivery workflows
• Continuously improve delivery workflows - Conduct retrospectives and co‑develop delivery processes that improve efficiency, eliminate friction, and drive measurable value.
• Contributes to refining delivery frameworks and feedback loops that support scalable team operations.
• Monitor individual program performance and delivery health using Agile metrics and practices - Track key performance indicators across projects to ensure milestones are being met, and identify coaching needs or resource misalignments