Top AI Jobs in Singapore

Leads APAC communications for S&P Global Energy by developing regional strategies, managing media relations, crafting internal and external content, coordinating interviews and events, measuring communications performance, and supporting crisis communications. The role builds relationships with journalists, analysts, influencers, senior leaders, and subject matter experts while translating complex energy and commodities market dynamics into compelling narratives.

Leads operational technology and automation strategy for a biologics manufacturing campus. Oversees automation architecture, engineering programs, suppliers, budgets, compliance, validation, startup readiness, and continuous improvement. Provides technical leadership across SCADA, PLC, DCS, IT/OT cybersecurity, digital manufacturing, and AI enablement. Partners with engineering, IT, operations, and global stakeholders while coaching automation engineers and supporting FDA inspections, cGMP expectations, and smart-factory transformation.

Owns strategic enterprise accounts in Singapore's financial services sector, selling AI security products and services. Responsibilities include engaging C-level customers, identifying cybersecurity and IT needs, managing account plans and forecasts, driving sales opportunities, partnering with resellers and system integrators, maintaining competitive market knowledge, and documenting customer information in Salesforce.

Design and advise on enterprise Agentic AI implementations that securely integrate probabilistic AI with deterministic business systems. Translate business processes into technical requirements, architect event-driven and API-first solutions, guide LLM and agent-framework deployments, and implement governance through guardrails, validation, human-in-the-loop checkpoints, and process redesign. Engage executives and stakeholders to communicate technical vision and support enterprise adoption.

Leads management reporting, planning, analysis, MIS strategy, data governance, forecasting, and performance management for a bank. Advises senior executives and finance leaders through actionable financial and business insights, drives reporting transformation using automation and visualization, oversees data integrity and remediation, and develops a high-performing MIS team. The role also partners with front-office stakeholders on profitability, productivity, growth, and efficiency initiatives.

Leads enterprise value measurement for AI, data, and digital investments. Establishes ROI, benefits realization, attribution, validation, and governance frameworks; validates financial and operational risk assumptions; consolidates value and investment reporting; and provides insights for senior management and governance forums. The role also drives adoption, continuous improvement, reporting automation, stakeholder enablement, and delivery of innovation and transformation initiatives.

Conduct research in Industrial AI, develop novel AI methods, formalize domain knowledge, prepare project requirements, write research documentation and publications, and support project performance. The role may mentor students and researchers while contributing to long-term research agenda development and implementation. A relevant master’s degree or equivalent research experience is expected, with bachelor’s degree holders considered if they have relevant work experience. The position is physically based in Singapore.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

Leads complex enterprise customer engagements as a technical authority for Databricks data and AI solutions. Owns architecture, consumption strategy, executive relationships, competitive positioning, migrations, real-time systems, and AI/ML platforms. Orchestrates cross-functional teams, mentors solutions architects, drives platform adoption and revenue growth, and contributes to technical thought leadership through workshops and customer-facing content.

Lead computational and AI/ML efforts for protein and enzyme engineering, including screening data foundations, sequence and structure modeling, method benchmarking, reusable analysis tools, and closed-loop design-build-test-learn workflows. Partner with experimental scientists, automation, software, and data engineering teams to transform screening results into actionable design recommendations and reusable data assets.

Develop and deploy AI and machine learning solutions, including generative AI copilots, recommendation systems, RAG, and agentic AI. Build predictive and generative models using structured and unstructured data, create data-driven visualizations, and collaborate with business stakeholders across domains. The role includes applying modern ML, cloud, MLOps, and real-time data technologies, communicating insights, and potentially managing a team.

Lead AI pilot and transformation programs for enterprise clients, including discovery, roadmap development, stakeholder alignment, capability building, metrics, and change management. Coach delivery teams on AI-augmented software development, help establish AI Centers of Excellence, and co-design multi-agent toolchains and automation. Support presales, thought leadership, and methodology development while integrating emerging AI tools into structured delivery practices.

Lead client AI transformation programs from discovery through deployment, including roadmaps, stakeholder alignment, capability building, metrics, and AI Centre of Excellence setup. Coach delivery teams on AI-augmented software development, co-design agentic toolchains and multi-agent systems, evaluate emerging AI tools, support presales, and contribute to thought leadership through articles, events, frameworks, and playbooks.

Lead Forward Deployed Engineering across APAC to design and deliver hybrid-cloud, Kubernetes-based AI platforms; bridge regional customer needs with global R&D and open-source communities; architect secure, compliant sovereign AI deployments; mentor senior engineers; drive upstream open-source contributions and regional developer engagement.

Supports technology-enabled assurance testing for anti-money laundering and sanctions risks. Responsibilities include designing continuous testing approaches, analyzing data, identifying control gaps and risk trends, developing dashboards, exploring automation and AI capabilities, preparing management reporting, documenting observations, supporting remediation follow-up, and collaborating with Compliance, Technology, Business, and Support stakeholders.

Own the backend and agent systems powering LLM products, including multi-turn conversations, tool calling, RAG, state management, evaluations, monitoring, and production reliability. Diagnose failures across models, knowledge systems, tools, and infrastructure; establish regression testing and quality measurement; and guide product and technical decisions. The role requires shipping and improving LLM features at scale, strong backend engineering, disciplined evaluation practices, and preferably Web3 experience.

Lead digital transformation, process improvement, and operational projects across banking operations. Gather requirements, coordinate cross-functional delivery, manage risks and milestones, document processes, facilitate UAT and change management, and report project progress. Provide operational backup, support business continuity, maintain controls, and help implement automation and workflow improvements. The role also includes presentations, training, stakeholder collaboration, and continuous improvement initiatives.

Drive long-term research and build production-ready enterprise AI: prototype and scale models, lead projects, validate with customers, collaborate with product and engineering to deliver large-scale generative AI and agent systems.

Lead and develop a team of Applied AI Engineers serving enterprise customers across Southeast Asia. Oversee AI solution design, production implementation, reliability, security, evaluation, adoption, and expansion. Coach engineers, handle technical escalations, establish prioritization and coverage models, develop reusable architectures and enablement, and translate customer needs into product feedback. Partner with executives and cross-functional teams while building scalable processes, measuring outcomes, hiring talent, and fostering an inclusive, high-performing organization.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Own customer outcomes for Singapore legal customers using AI solutions. Lead onboarding, implementation, training, adoption, success planning, ROI measurement, customer health monitoring, renewal readiness, and expansion identification. Build executive and cross-functional relationships, support proofs of concept, resolve issues, communicate project status, and translate customer feedback into actionable product and go-to-market insights.

Conduct independent technology, information security, cyber, and digital risk assessments of third-party service providers. Evaluate security controls, cloud and infrastructure risks, AI and digital asset risks, regulatory compliance, and assurance artifacts. Develop and improve third-party risk policies and frameworks, monitor risk trends, produce management reporting, support automation and data-driven analysis, provide stakeholder training, and advise senior management on mitigation strategies.

Oversee portfolios of Generative AI data operations projects, managing delivery, capacity planning, vendors, budgets, quality, risks, automation, and client reporting. Coach project managers and coordinators, collaborate with recruiting and finance, enforce data security and compliance, and improve processes across distributed teams.

Lead Multiplier’s company-wide AI strategy, shared AI platform, and customer-facing AI experiences. Build agent infrastructure, retrieval, tool access, evaluation, and safety systems; launch an AI agent that answers questions using customer data and eventually executes tasks. Lead a cross-functional team, establish AI development standards, and partner across product, engineering, support, and operations to deliver trusted, scalable AI capabilities.

Build and maintain end-to-end full-stack applications and cloud infrastructure incorporating AI and GenAI workloads. Integrate LLMs, RAG, AI agents, and agentic workflows into user-facing products. Design APIs, databases, CI/CD pipelines, containerized deployments, and infrastructure as code across major cloud platforms. Support secure, reliable, observable systems while serving as a technical contact for clients and operations teams and producing technical documentation.