Top AI Jobs in Singapore

Operate and monitor large-scale datacenter networks for AI workloads, lead incident response, troubleshoot GPU-cluster networking (jitter, NCCL throughput), manage tickets and change control, produce reports, and coordinate with R&D and customers.

Operate and harden Kubernetes-based AI/MaaS production environments; define SLOs, alerting, dashboards, and runbooks; improve rollout safety with canaries and fast rollbacks; drive GPU capacity planning; automate operations with Helm, Argo CD, operators and scripts; and partner to debug incidents from API edge to model workers.

Design and build scalable multi-agent AI systems that automate infrastructure and business workflows. Integrate agents with cloud services, APIs, Kubernetes, telemetry, and observability platforms to perform autonomous remediation, code generation, and system analysis. Develop agent memory and RAG systems, implement evaluation and security guardrails, and establish deployment and governance practices for agentic applications. Collaborate with infrastructure teams to integrate autonomous agents into resilient cloud platforms.

Join an 18-month graduate/early-career program to build large-scale AI cloud infrastructure: GPU VMs, bare-metal, managed Kubernetes, distributed training and inference, AI Agent platforms, observability, networking, storage, and automation for global AI workloads.

Design, deploy, and maintain CSI drivers and GPUDirect Storage integrations for high-performance file systems; implement NVMe caching and optimize IOPS/throughput/latency across containerized storage. Collaborate on RDMA/InfiniBand tuning, define Kubernetes storage policies and multi-tenancy isolation, implement monitoring/alerting, and mentor junior engineers.

Lead end-to-end delivery of multi-region AI cloud infrastructure and platform software projects, coordinating cross-functional teams, vendors, and leadership to meet timelines, budgets, and quality standards for large-scale GPU deployments and cloud platform releases.

Design and build interactive AI-powered prototypes for complex SaaS security and permission workflows. Partner with product leadership to translate feature decisions into UX flows, wireframes, high-fidelity interfaces, and production-ready components. Conduct user interviews and usability testing, iterate designs based on feedback, collaborate closely with engineers, and improve the design system. The role requires strong product thinking, browser-based prototyping skills, autonomy, and comfort with ambiguity.

Own strategic account growth and AI partnership development across enterprise and public-sector clients. Build executive relationships, create long-term account strategies, manage commercial performance, develop joint go-to-market initiatives with Microsoft and GitHub, coordinate executive engagements and events, and contribute to AI consulting offerings, thought leadership, and commercial playbooks.

Senior customer-facing AI leader who defines AI strategy, architects end-to-end LLM and RAG-based solutions, leads technical discovery and proof-of-value, drives enterprise AI adoption and governance, influences product roadmaps, and ensures successful production deployment and measurable business value across cloud-native and telecom environments.

Own paid acquisition across Google, Bing, Meta, and YouTube, scaling campaigns from creative production through launch, optimization, and attribution. Produce high-volume ad assets using AI tools, manage full-funnel campaigns, improve campaign processes, automate repetitive work, and analyze CAC, ROAS, payback, and product activation data. The role requires hands-on Google Ads expertise, creative production skills, subscription funnel experience, and strong ownership in a remote startup environment.

Owns data and AI governance initiatives within a technology unit, including operating-model design, policy and controls adoption, data quality management, assessment reviews, responsible data use, AI governance, risk monitoring, issue remediation, audit readiness, and stakeholder escalation. The role advises data domain leaders, coordinates with enterprise risk and data functions, and strengthens data governance culture across a complex, regulated banking environment.

Leads APAC-focused ecosystem market development for AI and data center infrastructure. Builds executive relationships across hyperscalers, NeoClouds, data center operators, contractors, integrators, submarine networks, and sovereign AI programs. Identifies market gaps, investment priorities, technology shifts, and growth opportunities, then translates ecosystem intelligence into recommendations for product, business, market, and solution strategy teams. Influences roadmaps and improves alignment across sales organizations without owning direct accounts or short-term sales targets.

Develops scalable backend applications, microservices, APIs, and LLM-powered features for risk technology. Responsibilities include prompt and context engineering, RAG, AI agents, vector databases, evaluation harnesses, guardrails, SQL and ORM development, full-stack contributions, CI/CD, deployment automation, monitoring, and DevOps. The role collaborates with stakeholders to translate technical and AI requirements into reliable production systems.

Lead AI risk assessments, identify and mitigate risks in AI projects, audit models and datasets for bias and explainability, implement responsible AI policies, and monitor regulatory developments. The role involves cross-functional collaboration, stakeholder communication, team leadership, coaching, and research across pharmaceutical, clinical, supply chain, and corporate applications.

Lead development and optimization of semiconductor fabrication processes, create and review process recipes and technical data, establish SOPs and FMEAs, integrate equipment/material capabilities, drive continuous improvement, mentor engineers, collaborate cross-functionally and with vendors, and contribute to patents and publications while ensuring safety and compliance.

Lead design and delivery of generative AI agents and architectures, build robust APIs and scalable systems, roadmap AI applications, collaborate cross-functionally, troubleshoot production issues, and drive internal efficiency and customer-facing AI solutions.

Lead end-to-end design and implementation of generative AI solutions and APIs to improve customer-facing and internal automation. Build scalable, high-concurrency backend systems, collaborate with cross-functional teams, set best practices, and mentor engineers while driving deployment and MLOps for production AI products.

Lead the development of AI and ML solutions for underwriting, manage a team of data scientists, and ensure compliance and governance in initiatives.

Creates AI-generated imagery, video, motion, and visual content for campaigns, social, digital, and retail. Leads GenAI visual development while maintaining brand aesthetics, collaborates with multidisciplinary creative teams, adapts existing assets, and establishes AI guidelines, workflows, prompts, and best practices. Explores emerging tools and trends, recommends creative applications, and builds GenAI capabilities across the wider creative team.

Develop and deploy production-grade AI and machine learning solutions, including agentic and multi-agent systems, scalable ML pipelines, and real-time inference services. Design microservices, APIs, event-driven architectures, and CI/CD processes for AI applications. Lead technical design, mentor engineers and data scientists, conduct code reviews, and collaborate with product and platform teams. Apply advanced techniques across NLP, computer vision, recommendation systems, and predictive analytics while improving model performance and reliability.

In this role, you will lead the development of generative AI solutions, ensure AI safety and trust, and facilitate workshops while collaborating with researchers and industry to advance AI adoption.

Lead discovery, rapid prototyping, and deployment of production-ready AI solutions for supply chain and manufacturing. Build Python-based RAG pipelines, semantic search, multi-agent workflows, data integrations, and enterprise platform connections. Engage frontline operations, translate business needs into technical requirements, manage agile delivery, and ensure prototypes are scalable and transferable to core engineering teams. Work across SAP, MES, shop-floor platforms, databases, telemetry, and unstructured data while collaborating with security, data, and architecture teams.

Lead technical strategy with channel partners across ASEAN to build repeatable Microsoft Cloud and AI Workforce offerings (Copilot, Power Platform, Agents). Drive architecture design, workshops, POCs, offer development, partner enablement, and co-sell execution to convert technical capability into scalable revenue and customer outcomes.

Leads data-driven industrial optimization projects from requirements gathering through deployment and monitoring. Responsibilities include building scalable data pipelines, integrating industrial data from IoT devices, sensors, test benches, and SCADA systems, performing data quality checks and exploratory analysis, developing machine learning models, creating Power BI and Flask dashboards, supporting digital twin simulations, and developing RAG-based chatbot solutions.

Conducts PVD process optimization, metal film property measurement, data analysis, hardware characterization, troubleshooting, and root cause analysis under engineering guidance. The internship provides hands-on experience with semiconductor manufacturing, PVD technology, process engineering, and complex equipment while developing critical thinking and technical communication skills.