Job Description

Why this role exists

The AI Center needs a single accountable leader for portfolio strategy and industrialisation-turning experiments into adopted products with controlled run‑costs, clear governance, and decision‑grade evidence. This role operationalises a “single‑door” direction: close the door on ad‑hoc tools and drive consistent, scalable AI product delivery through a governed factory model.

Portfolio scope

AI use‑cases moving through Innovation Board gates
Recipe.AI, Chef.AI, Portfolio.AI, Marketing Translation.
AI Center enablement services and assets
Innovation Board operating rhythm and gate criteria
AI Lab Principles/Playbook (PoC vs pilot vs MVP vs BAU)
AI Toolkit + Sandbox adoption (standard experimentation route)
Ethics enablement
FinOps/showback, cost governance, run‑cost strategy

Outcomes you will be measured on

Roadmap, investment logic, and value clarity
12–18 month portfolio roadmap with sequencing, dependencies, business cases (ROI + adoption assumptions), and operating model per product.
Clear prioritisation logic based on value, feasibility, risk, and run‑cost.
Innovation Board runs as a product factory
Board has a clear charter, RACI, cadence, scorecard (funnel volume, pass/fail rates, cycle time), and decision templates.
Every gate decision is supported by decision‑quality artifacts: data readiness, evaluation plan/benchmarks, security posture, cost forecast, adoption plan.
Service catalog clarity (standardisation at scale)
AI Lab services defined with SLAs, required artifacts, and volume forecasts (Sandbox, MLOps, Ethics, FinOps, AI CoE patterns).
“Default route” for experimentation is the Toolkit/Sandbox-exceptions are explicit and time‑boxed.
Value realisation discipline (BAU products)
Quarterly value reviews for BAU products (Portfolio.AI, Marketing Translation) with funded optimisation backlog and measurable KPI movement.
Governance scaled (risk, ethics, and delivery discipline)
Clear, enforceable principles distinguishing PoC vs pilot vs MVP vs GA; “done means” standards include wired release readiness, telemetry, and operational handover.
Joint‑success principles with vendors and business sponsors are explicit and measurable.
FinOps and run‑cost control
Cross‑charging model maintained; GPU/compute strategy options presented early (trade‑offs among performance, cost, and reliability).
No “silent run‑cost blowups”: predictable budgets and proactive mitigations.
Singapore government co‑funding success
Maintain the co‑funding deliverable map (milestones, KPI targets, eligible cost tracking).
Produce structured quarterly reporting, demo days, and audit‑ready evidence packs.
Manage expectations and stakeholder engagement with government counterparts and ecosystem partners.

What You Do

Portfolio strategy and prioritisation
Define product strategy per initiative: problem statement, target users, adoption plan, KPIs, operating model.
Run prioritisation with Sonal/Dan; explicitly manage trade‑offs among value, feasibility, risk, time‑to‑market, and run‑cost.
Governance and operating model
Own Innovation Board mechanics: gate criteria, templates, decision logs, scorecards, and escalation paths.
Define and enforce portfolio “definition‑of‑done” standards (including data/model contracts, security controls, observability, BAU handover).
Ensure the Toolkit/Sandbox is not optional “nice-to-have,” but the standard platform path.
Stakeholder leadership (business + architecture + security)
Drive alignment and sign‑offs with CDAO LT and Enterprise Architecture; ensure solution strategy is board‑endorsed and operationally viable.
Own narrative and executive‑ready decision packs: trade‑offs, cost, risk, adoption constraints, and recommended decision.
Vendor and partner shaping (without doing procurement’s job)
Translate roadmap into outcome‑based requirements and success metrics that can be contracted.
Ensure vendor delivery aligns with “industrialisation” expectations (security-by-design, documentation, monitoring, handover, cost controls).
Define joint success measures and governance cadence with partners.
Adoption, ethics, and community flywheel
Drive enterprise enablement motions that materially affect adoption: ethics hub, Copilot/GenAI usage guidance, community ideation intake, playbooks for responsible AI rollout.
Ensure adoption is measurable (telemetry + feedback loops) and drives roadmap decisions.