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Open nowPosted 2 days ago

AI Lead

MyCareersFuture89,443 open roles

Pay
SGD 15,000 – SGD 20,000 a Monthly
Where
Central, Singapore
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Your applicationOpen nowAI LeadMyCareersFuture · Central, Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on MyCareersFuture's own form.

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The clock on this job

Early applications get read.

9.0% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 7 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.9%3 days
  3. 9.0%7 days
  4. 15.5%14 days
  5. 34.1%30 days
This job: posted 2 days ago

MyCareersFuture median: 7 days open

The posting

Maker Lab is looking for an AI Lead to serve as the regional catalyst and architectural owner for production-grade Applied AI, Generative AI, and Agentic Decision Intelligence across six JAPAC sub-regions. Working within the intersection of Strategy & Operations and Enterprise Technology teams, we’re looking for a builder who can drive the 0-to-1 incubation and 1-to-N enterprise scaling of intelligent systems that eliminate analytical latency and orchestrate autonomous revenue intelligence for our embedded teams and clients.

As an in-housing agency, people are a large part of our organisation, and we’re looking for someone who can balance our people-first principles with innovation, guiding mission-critical commercial decisions for executive leadership and ensuring our clients and teams can work effectively and efficiently to drive better results.

  • AI Incubation & 0-to-1 Architecture: Lead the charter, design, and prototyping of cutting-edge Agentic AI workflows, Human-in-the-Loop (HITL) platforms (e.g., Gemini-powered automated reporting), and autonomous decision engines from concept validation to scalable enterprise deployment.
  • Executive Advisory & Problem Scoping: Partner directly with regional C-suite and VP-level stakeholders across 350K+ accounts to translate ambiguous commercial bottlenecks into high-ROI AI, machine learning, and BI transformation initiatives.
  • Revenue & Predictive Intelligence: Oversee the architecture of multi-stage predictive systems (XGBoost propensity frameworks, self-tuning scenario models, and BigQuery outlier detection logic) that shift enterprise GTM motions from reactive reporting to prescriptive targeting.
  • AI Engineering, Governance & Scalability: Establish enterprise-grade standards for LLM observability, model evaluation (AUROC, SHAP interpretability), automated data lineage, and ethical AI governance to guarantee single-source-of-truth reliability across all distributed decision engines.
  • Incubator Operations & Ecosystem Acceleration: Manage the intake, prioritisation, and sprint velocity of experimental AI initiatives; mentor senior data scientists and ML engineers while driving AI literacy across cross-functional commercial teams.

You:

  • Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or an equivalent quantitative discipline.
  • 12+ years of combined experience across Data Science, BI Transformation, and Enterprise AI Strategy, with 5+ years driving regional programs across JAPAC.
  • Production AI Delivery: Demonstrated track record in architecting and deploying GenAI/LLM pipelines, multi-agent frameworks, or automated decision intelligence platforms into enterprise production.
  • Executive Influence: Proven success acting as a trusted advisor to senior regional leadership (VP/Director level), shaping operational OKRs and multi-year GTM roadmaps.
  • Cloud & Technical Stack: Advanced proficiency in Python, SQL, Cloud Data Warehousing (BigQuery), Machine Learning libraries (XGBoost, Scikit-Learn, TensorFlow), and Cloud ecosystems (GCP).
  • GenAI & Agentic Systems (Preferred): LLM fine-tuning, RAG frameworks, prompt orchestration, Agentic tool-use, Gemini Pro ecosystem.
  • Decision Modelling & Architecture (Preferred): Dynamic scenario planning engines, econometric forecasting, Winsorized trend analysis, SHAP explainability, Data Vault 2.0, multi-source CRM/ERP integration (Salesforce, SAP), BI platforms (Looker Studio, Power BI).
  • Certifications (Preferred): Google Cloud Professional Machine Learning Engineer (PMLE) or Google Cloud Generative AI Leader.
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