AI Lead

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.