Top Tech Jobs & Startup Jobs in Singapore

Build, deploy, maintain, and monitor scalable machine learning systems, infrastructure, pipelines, and applications. Collaborate with data scientists, engineers, clients, and stakeholders to deliver ML solutions, lead functional workstreams, explore emerging tools, address technical challenges, and mentor team members. Apply MLOps, CI/CD, cloud and on-premises infrastructure, model training, deployment, monitoring, and evaluation practices while contributing to the organization’s machine learning strategy.

Infrastructure Engineer responsible for designing, implementing, and improving enterprise and web-scale infrastructure. The role involves cloud platforms, DevOps, Infrastructure as Code, application hosting, CI/CD, monitoring, security, and automation. The engineer collaborates with software delivery teams and clients, develops technical roadmaps, establishes continuous delivery processes, and advises engineering leadership on scalable, secure solutions.

Designs, implements, and improves client infrastructure and cloud platforms through hands-on DevOps, platform engineering, automation, and continuous delivery. The role develops technical roadmaps, manages Kubernetes and AWS environments, establishes infrastructure controls, monitors delivery quality, and advises client engineering leadership. It also requires collaboration across technical and business teams, consulting expertise, and the ability to communicate complex concepts to nontechnical stakeholders.

Leads AI engineering teams delivering scalable, production-ready generative AI and agentic solutions. Provides architectural and technical direction, oversees RAG pipelines, vector database integration, model optimization, testing, guardrails, responsible AI, monitoring, and documentation. Collaborates with product and business stakeholders, reviews designs and code, mentors engineers, and shapes technical roadmaps and engineering practices.

Designs, implements, and improves client infrastructure, hosting platforms, cloud environments, and application delivery processes. The role assesses existing systems, develops technical roadmaps, establishes continuous delivery controls, and advises clients on DevOps, platform engineering, security, and infrastructure automation. It also requires collaboration with engineering, infrastructure, network, security, and IT leadership teams while communicating technical concepts to nontechnical stakeholders.

Lead hands-on AIOps architecture and engineering for APAC client engagements. Design production-grade observability, intelligent alerting, AI-assisted triage, RCA, retrieval, and runbook automation solutions. Build integrations, data pipelines, agentic workflows, evaluation pipelines, and cloud infrastructure while applying software engineering, SRE, DevOps, testing, and governance practices. Advise clients, support technical pre-sales and proposals, mentor engineers, and connect regional projects with global AIOps capabilities.

Design, build, and deploy production generative AI applications using RAG, agents, and multi-agent systems. Collaborate with AI/ML, software, product, design, and data teams to deliver scalable and reliable solutions. Make architectural decisions, optimize performance and cost, review code, apply cloud and LLMOps practices, and mentor junior engineers while contributing to engineering standards.

Lead Quality Analyst responsible for developing quality strategies across products and teams, shifting quality left, managing delivery risks, conducting exploratory and cross-functional testing, and driving test automation standards. The role coaches engineers and other team members, improves testability and software quality, applies metrics and industry standards, and advocates quality practices with clients, internal teams, and the broader technology community.