This role sits within NCS AI Central's (AIC) Forward Deployed Engineering (FDE) model — the combined capability that takes AI solutions from proof-of-concept through to hardened production systems. As AI Delivery Project Manager / Scrum Master, you own delivery of the FDE lifecycle for your squad (Discover → POC → POV → PRR → Scale → Operate), run Agile ceremonies tuned for AI/Gen AI's iterative, evidence-driven nature, and act as the primary link between engineering delivery, AI Mission, AI Experience, and client/business stakeholders — across both fast-moving FDE engagements and steady-state system development and maintenance work.
What will you do:
1. FDE Lifecycle Ownership
- Own delivery of the squad's engagement through the FDE lifecycle — Discover, POC, POV, PRR, Scale, Operate — tracking where each workstream sits and what's needed to move it to the next gate.
- Plan and execute short-cycle POCs/POVs from concept to evaluation, including receiving and refining scoped opportunities handed off from AI Mission.
- Define minimal scope, success criteria, and timelines appropriate to each lifecycle stage; prioritize features based on value, feasibility, and constraints.
- Coordinate the PRR (Production Readiness Review) gate as the delivery-side owner — tracking the five-pillar checklist (Evaluation & Quality, Security/Governance/Compliance, Model & Token Strategy, and others) to readiness, in partnership with the AI Architect and AI/LLM Specialist.
2. Agile Leadership for AI Squads (Scrum Master)
- Run lightweight Agile ceremonies — daily stand-ups, sprint planning & refinement, demo reviews, and retrospectives — adapted for AI/Gen AI work, where "done" often means a measured evaluation result, not just shipped code.
- Promote velocity, transparency, and continuous improvement across experimentation-heavy sprints.
- Unblock progress quickly — including chasing down data access, model access, or compliance sign-offs that commonly stall AI engagements — and minimize ceremony overhead.
3. AI Delivery Risk & Feasibility Management
- Maintain a working risk register specific to AI delivery — hallucination/accuracy risk, data quality dependency, model/token cost exposure, and latency — and translate these into scope and timeline decisions the squad can act on.
- Advise stakeholders directly when a request is technically impractical, high-risk, or better served by a non-Gen AI approach, drawing on input from the AI Engineer, AI/LLM Specialist, and Data Scientist.
- Maintain working awareness of the Gen AI model landscape — including China-origin models (DeepSeek, Qwen, GLM) as increasingly viable, cost-effective options — sufficient to have an informed feasibility conversation with technical leads and clients.
- Own secure software delivery and governance practices as a standing checkpoint through the lifecycle, not just at PRR — flagging compliance gaps (IM8, PDPA, sector-specific) early enough to act on them.
4. Stakeholder Alignment Across the FDE Model
- Act as the delivery-side connective tissue across AI Mission (opportunity handoff), AIIS (build/scale/govern), and AI Experience (design/adoption) for the squad's engagement.
- Translate problem statements into achievable POC/POV plans, and manage expectations around what can be delivered, when, why, and at what lifecycle stage.
- Facilitate clear communication between business and engineering, bringing a consulting mindset and customer-first attitude to stakeholder interactions.
- Socialize learnings, outcomes, and next steps; present outcomes and lifecycle-stage recommendations to stakeholders and decision makers up to Director level.
5. Outcomes, Evaluation & Reporting
- Track POC/POV performance against defined success criteria, incorporating evaluation evidence (accuracy, hallucination rate, cost-per-query) from the AI/LLM Specialist rather than relying on qualitative impressions alone.
- Document findings, results, and lifecycle-stage recommendations (advance, iterate, or stop) clearly for both technical and business audiences.
6. FDE & Development/Maintenance Coverage
- During FDE engagements: run lightweight, fast-cycle Agile ceremonies and POC/POV plans that keep pace with rapid client iteration, and drive the engagement toward a clean PRR gate decision.
- During system development & maintenance engagements: shift cadence toward disciplined delivery tracking and stakeholder reporting appropriate for live production systems, coordinating ongoing model/cost monitoring handoffs with LLMOps and AI FinOps.
- Coordinate work across Application Architect, Fullstack Developer, Cloud Engineer, AI Engineer, and Data Scientist roles; manage remote or offshore collaboration; and track resource use and budgets across both short POC cycles and longer production engagements.
We are hiring at two levels for this role. All responsibilities above apply to both; the distinction is in scope of ownership, years of experience, and seniority of judgement expected.
AI Delivery Project Manager / Scrum Master
- 3–5 years of Project Management / Scrum Master experience, including at least 1 year on AI/Gen AI engagements. Runs Agile ceremonies and POC/POV delivery for one squad at a time, under guidance from a Senior AI Delivery PM or engagement lead.
- Manages stakeholder communication within a defined engagement; escalates cross-engagement resourcing, scope conflicts, or PRR gate risks to senior team members.
Senior AI Delivery Project Manager / Scrum Master
- 7+ years of experience, including sustained delivery of AI/Gen AI engagements at scale. Owns delivery governance and the Discover→POC→POV→PRR→Scale→Operate lifecycle across multiple squads or engagements.
- Engages up to Director-level stakeholders independently, chairs PRR gate reviews from the delivery side, and mentors junior AI Delivery PMs/Scrum Masters.
Qualifications
The ideal candidate should possess:
- 3+ years of Project Management / Scrum Master experience, including at least 1 year delivering AI/Gen AI engagements specifically (see Role Levels for the split between AI Delivery PM/Scrum Master and Senior).
- Experience planning and executing short-cycle POCs/POVs or Agile delivery cycles, including running Scrum ceremonies (stand-ups, sprint planning, demos, retrospectives).
- Working understanding of an AI/Gen AI delivery lifecycle (e.g. Discover→POC→POV→PRR→Scale→Operate or equivalent) and what "production-ready" means for an AI system, beyond a working demo.
- Strong stakeholder management and communication skills, comfortable engaging up to Director level.
- Working understanding of Generative AI capabilities and constraints (accuracy, hallucination, data quality, latency/cost trade-offs) sufficient to actively manage delivery risk, not just describe it.
- Comfortable coordinating distributed/offshore teams and tracking budgets across both short POC cycles and production-scale engagements.
Preferred Qualifications
- Direct experience coordinating or participating in a Production Readiness Review (PRR) or equivalent AI governance gate.
- Awareness of secure software delivery and governance practices, particularly for gov-adjacent engagements (IM8, PDPA).
- Experience presenting outcomes and recommendations to senior stakeholders and decision makers.
- Exposure to Singapore Government GCC/HCC engagement contexts.
Tech Stack (Illustrative)
- Delivery & Collaboration: Jira, Confluence, or equivalent Agile tooling
- Reporting: Standard reporting/dashboarding tools for tracking POC/POV outcomes and PRR gate status
Why Join NCS
We are driven by our AEIOU beliefs—Adventure, Excellence, Integrity, Ownership, and Unity—and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.
Together, we make the extraordinary happen.
Learn more about us at ncs.co and visit our LinkedIn career site.
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