AI Mission Leader

NCS PTE. LTD.; Singapore; On-site; SGD 260,000 - 340,000; Full time

Job summary

NCS PTE. LTD. seeks an AI Mission Leader to translate complex domain problems into measurable AI outcomes, set mission direction, and align cross-functional teams to deliver high-impact AI solutions across medicine and GenAI transformation.

You will define KPIs, manage executive stakeholders, govern AI programs, ensure responsible deployment, and drive adoption through change management and workforce readiness.

Qualifications

• Executive leadership delivering complex technical programs with measurable business outcomes.
• Ability to translate domain challenges into AI solutions, including problem definition, metric design, and delivery planning.
• Strong technical fluency in applied AI/ML and GenAI concepts (model capabilities/limits, evaluation, data pipelines, deployment considerations).
• Experience leading multi-disciplinary teams and influencing without authority across senior stakeholders.
• Proven track record of shipping production AI systems in regulated and/or high-stakes environments (healthcare preferred).
• Ability to manage risk across privacy, security, compliance, and safety, with a pragmatic approach to responsible AI.

Responsibilities

• Frame ambiguous, high-stakes domain problems into clear AI mission objectives, success metrics, and delivery roadmaps.
• Build and manage executive-level relationships across customers, partners, and internal leadership; translate needs into actionable AI programs.
• Prioritize initiatives across domains (e.g., general medicine, GenAI transformation), balancing impact, feasibility, risk, and time-to-value.
• Lead cross-functional teams (product, engineering, data science, design, security, compliance) to deliver production AI systems.
• Establish governance, delivery cadence, and decision-making frameworks to keep programs on track.
• Define KPIs/OKRs and ensure ongoing monitoring of model/business performance; drive iteration based on evidence.
• Responsible AI: Ensure safety, privacy, regulatory, and ethical requirements are embedded in design, training, evaluation, and deployment.
• Change management: Drive adoption and transformation, including training, workflow redesign, and stakeholder communications.
• Talent and culture: Hire, coach, and retain high-performing AI leaders; set a culture of clarity, rigor, and mission focus.

Skills

Executive leadership

Problem framing

AI/GenAI fluency

Stakeholder management

Delivery of AI systems

Risk & responsible AI

Job description

Role Summary

The AI Mission Leader is a senior executive responsible for translating complex domainproblems and stakeholder relationships into measurable AI outcomes. This leadersets mission direction, aligns cross-functional teams, and ensures delivery ofhigh-impact AI solutions across priority domains such as AI in general medicineand enterprise GenAI transformation. The role is benchmarked against top-tiermission- driven organizations (e.g., Palantir, Anthropic) with an emphasis onrigorous problem framing, execution excellence, and responsible deployment.

Key Responsibilities

• Mission definition andoutcomes: Frame ambiguous, high-stakes domain problems into clear AI missionobjectives, success metrics, and delivery roadmaps.
• Stakeholder leadership: Buildand manage executive-level relationships across customers, partners, andinternal leadership; translate needs into actionable AI programs.
• AI strategy and portfolioownership: Prioritize initiatives across domains (e.g., general medicine, GenAItransformation), balancing impact, feasibility, risk, and time- to-value.
• End-to-end delivery: Leadcross-functional teams (product, engineering, data science, design, security,compliance) to deliver production AI systems.
• Operational excellence: Establish governance, delivery cadence, and decision- making frameworks to keepprograms on track.
• Measurement and accountability: Define KPIs/OKRs and ensure ongoing monitoring of model/business performance;drive iteration based on evidence.
• Responsible AI: Ensure safety,privacy, regulatory, and ethical requirements are embedded in design, training,evaluation, and deployment.
• Change management: Driveadoption and transformation, including training, workflow redesign, andstakeholder communications.
• Talent and culture: Hire,coach, and retain high-performing AI leaders; set a culture of clarity, rigor,and mission focus.

Scope /Example Missions

• General medicine: Clinicaldecision support, care pathway optimization, patient triage, documentationautomation, population health analytics, operational forecasting.
• GenAI transformation: Enterprise knowledge assistants, workflow copilots, customer supportautomation, content and code generation enablement, secure retrieval- augmentedgeneration (RAG) solutions.
• AI platform enablement: Standardized evaluation, MLOps/LLMOps, monitoring, data quality programs,reusable components to accelerate delivery across teams.

Qualifications

• Executive leadership experiencedelivering complex technical programs with measurable business outcomes.
• Demonstrated ability totranslate domain challenges into AI solutions, including problem definition,metric design, and delivery planning.
• Strong technical fluency inapplied AI/ML and GenAI concepts (model capabilities/limits, evaluation, datapipelines, deployment considerations).
• Experience leadingmulti-disciplinary teams and influencing without authority across seniorstakeholders.
• Proven track record of shippingproduction AI systems in regulated and/or high- stakes environments (e.g.,healthcare preferred).
• Ability to manage risk acrossprivacy, security, compliance, and safety, with a pragmatic approach toresponsible AI.

SuccessMetrics (Examples)

• Business impact: Revenuegrowth, cost reduction, cycle-time reduction, quality improvements attributableto AI programs.
• Adoption: Useractivation/retention, workflow penetration, stakeholder satisfaction, trainingcompletion.
• Model performance: Task-specific accuracy/utility, hallucination/error rates, calibration,robustness, bias/fairness measures.
• Operational reliability: Latency, uptime, incident rate, monitoring coverage, model drift detection andresponse time.
• Delivery execution: On-timemilestones, scope control, risk closure rate, cross-team alignment health.

CoreLeadership Qualities (Benchmarked to Top AI Organizations)

• Mission-first orientation: Relentless focus on real-world outcomes and measurable impact.
• Exceptional problem framing: Turns ambiguity into crisp goals, constraints, and decision points.
• High-standards execution: Drives pace, quality, and accountability; raises the bar for technical andoperational rigor.
• Systems thinking: Understands end-to-end socio-technical systems, not just models.
• Credible technical leadership: Communicates with depth; earns trust of senior engineers, researchers, anddomain experts.
• Stakeholder mastery: Builds durable relationships, handles conflict productively, and aligns incentives.
• Product intuition: Understands user workflows, adoption barriers, and change management.
• Integrity and safety mindset: Embeds responsible AI, security, and privacy into delivery.
• Talent magnet: Attracts and develops high-caliber teams; sets a culture of learning and ownership.

ReportingLine and Collaboration

• Reports to a C-level executive(e.g., CEO, CTO, Chief Data/AI Officer) and partners closely with Product,Engineering, Clinical/Domain Leadership (for medicine),
• Security, Legal/Compliance, andgo-to-market leadership. Serves as an executive- facing leader for missionoutcomes and portfolio performance.