Top AI Engineer Jobs in Singapore

Leads a team developing and productionizing predictive, machine learning, deep learning, and GenAI solutions for semiconductor manufacturing and HBM product engineering. Responsibilities include yield and reliability modeling, large-scale data pipelines, MLOps, model monitoring and drift control, distributed analytics, deployment, and engineering decision support. The role also requires mentoring engineers, setting technical direction, collaborating cross-functionally, and translating model outputs into improvements in quality, cost, cycle time, and manufacturing efficiency.

The role involves developing AI and ML solutions for semiconductor workflows, training Citizen Data Scientists, and integrating intelligent agents into engineering processes.

Senior software engineer builds, deploys, and supports IT applications for semiconductor manufacturing. Owns full application lifecycle, uses AI-assisted tools, implements CI/CD, monitors system performance, coordinates worldwide releases, provides L3 24/7 support, and works in clean-room environments to improve productivity and reliability.

Designs, develops, deploys, and governs AI-powered products, intelligent workflows, and autonomous multi-agent systems for HR and People organizations. Builds integrations across Workday, ServiceNow, Microsoft platforms, APIs, and enterprise data sources. Develops reusable AI frameworks, orchestration, tool calling, retrieval, monitoring, and evaluation capabilities while ensuring security, privacy, compliance, and responsible AI standards. Partners with business and technology leaders to identify transformation opportunities and deliver scalable solutions across recruiting, onboarding, employee services, learning, talent management, and workforce planning.

Designs and delivers agentic AI systems that transform complex business processes into autonomous, scalable workflows. Responsibilities include process decomposition, AI architecture, agent and tool orchestration, prompt and context strategy, prototyping, security controls, human-in-the-loop design, testing, cross-functional delivery, value measurement, and mentoring. The role requires collaboration with business, architecture, security, platform engineering, and project management teams through production release.

Leads the redesign of complex business processes into autonomous, agentic AI systems. Responsibilities include process decomposition, AI architecture, agent workflow development, prototyping, integration, security controls, human-in-the-loop design, testing, production delivery, value measurement, and mentoring. The role collaborates with business, architecture, security, platform engineering, and project management teams to deliver scalable generative AI solutions.

Designs and delivers agentic AI systems that transform complex manual business processes into secure, scalable autonomous workflows. Responsibilities include process decomposition, AI architecture, agent and prompt design, integrations, prototyping, testing, human-in-the-loop controls, least-privilege security, cross-functional delivery, value measurement, and mentoring. The role requires strong business-process redesign experience alongside hands-on AI/ML and LLM system development.

Build scalable batch and real-time ETL pipelines and trusted customer-data foundations for analytics, machine learning, operational decision-making, and AI applications. Develop data models and products across warehouses and cloud infrastructure, using technologies such as Databricks, dbt, Spark, Kafka, and Flink. Collaborate with globally distributed teams on complex technical work.

Build and own scalable batch and real-time ETL pipelines for Airwallex’s Customer Data Platform. Develop trusted data foundations, warehouses, models, and data products supporting analytics, machine learning, operational decisions, business intelligence, and AI applications. Partner with globally distributed teams to deliver complex technical solutions using modern data infrastructure and streaming technologies.

Build and deploy full-stack AI applications for smart manufacturing, including data pipelines, machine learning models, APIs, web interfaces, LLM integrations, automation tools, and observability. Develop containerized solutions with Docker and Kubernetes/OpenShift, contribute to CI/CD and MLOps practices, integrate robotics and manufacturing systems, and apply Responsible AI controls. Collaborate with data scientists, software engineers, and manufacturing stakeholders to improve operational decision-making and autonomous operations.

Develop and maintain enterprise AI platforms and shared services, including reusable frameworks, integrations, APIs, and AI capabilities. Partner with delivery, innovation, engineering, architecture, and business teams to accelerate AI solution deployment. Support platform reliability, scalability, security, governance, privacy, responsible AI, troubleshooting, documentation, and operational excellence. Evaluate emerging technologies such as LLMs, AI agents, MCP, RAG, and cloud AI services while contributing to platform roadmaps and technical best practices.

Develops and supports software and AI-enabled IT solutions for semiconductor manufacturing. Responsibilities include requirements analysis, coding, testing, CI/CD, application lifecycle management, global releases, UAT, monitoring, maintenance, system recovery, and L3 operational support. The role requires collaboration with users and engineering teams, occasional cleanroom work, and participation in 24/7 support rotation while applying approved AI tools securely and responsibly.

Develop and deploy machine learning models, predictive analytics, and agentic AI solutions for semiconductor manufacturing and engineering. Build scalable data pipelines and ML workflows using large-scale manufacturing datasets to improve yield, quality, reliability, cycle time, and cost. Integrate AI agents with enterprise platforms, mentor Citizen Data Scientists, lead technical initiatives, and support production deployment, MLOps, innovation, and AI adoption across Product Engineering.

Design, deploy, and optimize agentic AI workflows and integrations for enterprise customers. Lead implementations from scoping through adoption, connect agents to customer data and systems, establish prompts, evaluations, guardrails, and human oversight, and coordinate engineering, data science, product, and customer success teams. Serve as the primary technical customer partner while managing roadmaps, requirements, delivery risks, and measurable implementation outcomes.

Build and operate AI-powered application security systems, including secure code review, threat modeling, vulnerability triage, remediation automation, and agent governance. Lead security design reviews for LLM, RAG, MCP, and agentic systems; implement identity, access, sandboxing, audit, and guardrail controls; defend against AI-specific threats; and partner with engineering teams to improve secure-by-default practices and measurable AppSec outcomes.

Conduct robotics research involving probabilistic perception, uncertainty-aware algorithms, and robust manipulation. Develop and benchmark C++ and Python software, integrate robotic hardware and sensors, validate systems experimentally, maintain open-source repositories, prepare patent disclosures and research manuscripts, manage laboratory infrastructure, follow safety standards, and co-guide student researchers.

Designs and deploys AI-assisted solutions, automation, data pipelines, and analytics for Data Loss Monitoring. The role translates control requirements into secure workflows, data products, detection capabilities, dashboards, and investigation tools. Responsibilities include Python and SQL development, ETL/ELT, AI/LLM integration, orchestration, production support, governance, testing, stakeholder management, and risk-based monitoring within a regulated banking environment.

Leads hands-on design and delivery of production AI and ML systems, including data pipelines, model training, serving, monitoring, evaluation, and MLOps. Engages clients to translate business needs into AI solutions, develops value cases, leads technical workstreams, and manages and mentors engineering teams. Responsibilities also include responsible AI governance, compliance safeguards, innovation, proposal support, and enterprise platform integrations.

Leads enterprise AI transformation at executive and portfolio level while maintaining deep technical credibility. Defines AI strategy, architecture standards, business cases, governance, and measurable outcomes; oversees global programs, commercial performance, sales growth, strategic partnerships, and practice development. Builds and leads senior engineering teams, establishes reusable AI frameworks, drives responsible AI and innovation, and engages CXOs, boards, hyperscalers, and industry stakeholders.

Designs and delivers customer-facing technical engagements, including strategy sessions, architecture workshops, prototypes, and AI transformation initiatives. Leads discovery, solution architecture, technology selection, and cross-platform cloud integration. Advises customers and internal sales teams on Azure AI capabilities, security, scalability, and performance while coordinating cross-functional stakeholders and shaping strategic account plans.

Supports LaserJet hardware qualification and validation through test automation, engineering data analytics, and AI-enabled workflows. Develops scripts, dashboards, and tools for test execution, data collection, reporting, troubleshooting, and anomaly detection. Prototypes generative AI solutions and agents, collaborates with hardware and test engineers, and documents and validates tools for broader adoption.

Design and build production-ready enterprise AI architecture blueprints and open-source Quickstarts, integrate and benchmark model serving and telemetry, ensure secure, compliant deployments, and co-develop integrations with partners.

Lead design, implementation, and productionization of enterprise AI solutions on Red Hat AI Platform and OpenShift across APAC. Deliver end-to-end AI workloads (data pipelines, training, LLM serving, inference), drive pilot-to-production, implement responsible AI controls, mentor team members, and produce architecture and operational documentation.

Build and deploy AI/ML solutions for APAC local rates Sales & Trading, focusing on pricing optimization, bid-offer calibration, risk management, dashboards, alerts, and generative AI applications. Develop data pipelines, APIs, and production tooling using market, trade, and client data. Partner directly with traders, sales professionals, quantitative researchers, compliance, and risk teams to deliver commercially impactful solutions in a fast-paced trading-floor environment.

Lead production AI initiatives including LLM agents, AI drafts, and a shared Context Engine. Own architecture decisions, evaluation systems, guardrails, observability, reliability, and quality measurement. Deliver major AI projects from design through production while providing cross-functional technical leadership and improving engineering standards. Build backend and platform infrastructure using Python, Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.