Total 6 system engineer job vacancies in Engineering category in Singapore

We are looking for an Engineering Manager / Lead Software Engineer to take on complex and meaningful technical challenges in the public sector, driving digital transformation that directly improves lives at scale.

In this role, you will be responsible for setting technical direction, shaping engineering processes, and ensuring delivery of one or more products owned by your team. You will also play a key role in building an engineering culture that values excellence, collaboration, and long-term impact.

Job Responsibilities:

• Defining your team’s engineering vision, strategy, and roadmap in alignment with broader organizational goals.
• Staying on top of industry trends, with strong knowledge of how systems should be architected, engineered, and maintained at scale.
• Designing and guiding the implementation of systems across SaaS solutions, leveraging cloud technologies where appropriate.
• Partnering with stakeholders to prioritize and manage product roadmaps, ensuring incremental and effective delivery towards long-term vision.
• Creating and maintaining a technical plan that anticipates future product and infrastructure needs.
• Coaching and mentoring engineers through regular feedback, supporting professional growth and career development.
• Driving adoption of best practices in quality, reliability, performance, and security within your teams.
• Encouraging strong engineering culture and introducing tools/processes that maximize effectiveness and impact.
• Actively identifying and initiating high-value engineering initiatives that contribute to the public good.
• Contributing to recruitment, particularly for senior technical roles.

Job Requirements:

• Proven experience building and operating large, high-availability software systems at scale.
• At least 10 years of development experience, with 5+ years coaching and mentoring engineering teams of 5+ people.
• Experience with modern full-stack application development, spanning contemporary front-end frameworks and scalable backend services across multiple programming languages.
• Hands-on technical expertise across the technology stack, including infrastructure, client-side, backend services, APIs, databases, performance, and data.
• Strong background in end-to-end system development, from user interfaces through backend and integration layers.
• Familiarity with Agile development, modular design, automation, TDD, CI/CD pipelines, pair programming, and infrastructure automation.
• Exposure to cloud platforms (e.g. AWS, Azure) and container technologies (e.g. Docker, Kubernetes).
• Excellent understanding of engineering leadership, balancing technical expertise with the soft skills needed to inspire and guide teams.
• Passion for engineering craftsmanship, teamwork, and creating meaningful impact through technology.
• Strong ability to lead teams toward achieving ambitious goals together.

Our client is a fast-growing AI company building enterprise-grade agentic automation solutions for large organizations. They are looking for a hands-on, client-facing AI engineer to work directly with enterprise clients and bring AI-driven automation workflows into production.

This role is best suited for a strong engineer who enjoys solving ambiguous customer problems, working close to real business operations, and moving from discovery to implementation quickly. You will help clients identify where AI agents can create practical impact, then design, build, integrate, deploy, and iterate solutions within complex enterprise environments.

You will work across backend engineering, solution design, integrations, data flows, deployment, and customer engagement, with a strong focus on reliability, business value, and production outcomes.

Key Responsibilities

• Partner directly with enterprise customers to understand their workflows, pain points, technical environments, and success criteria.
• Translate ambiguous business problems into clear technical plans, solution designs, and production-ready implementations.
• Build, configure, and deploy AI agents and automation workflows that connect with customer systems, data sources, APIs, and business processes.
• Own the delivery lifecycle from discovery and scoping through build, testing, launch, monitoring, and ongoing iteration.
• Write high-quality code for backend logic, integrations, workflow automation, data handling, and deployment requirements.
• Work with real customer data and production environments to test performance, measure outcomes, and improve solution effectiveness.
• Collaborate with product and engineering teams to improve the platform based on customer needs, deployment learnings, and field feedback.
• Run technical workshops, guide customers through implementation decisions, and explain technical trade-offs clearly to both technical and non-technical stakeholders.
• Identify repeatable patterns, create documentation, improve internal tools, and help scale delivery practices as the team grows.
• Take ownership of reliability, performance, maintainability, and long-term customer success after deployment.

Requirements

• Minimum 6 years of experience in software engineering, AI engineering, implementation engineering, technical consulting, or similar hands-on technical roles.
• Strong backend engineering fundamentals, including system design, APIs, integrations, data flows, and production systems.
• Experience with AI agents, LLM applications, automation platforms, workflow tools, or data-heavy enterprise systems.
• Experience building or deploying AI solutions in complex customer environments, especially where requirements are ambiguous or evolving.
• Comfort working directly with enterprise customers, including business, operations, IT, and technical stakeholders.
• Ability to quickly understand customer workflows and identify where automation or AI can deliver practical business impact.
• Strong ownership mindset, with the ability to create clarity, drive decisions, and move projects forward independently.
• Clear communication skills, with the ability to explain technical concepts, implementation plans, risks, and trade-offs in a practical way.
• Experience working with production systems, including testing, debugging, monitoring, performance improvement, and ongoing iteration.
• Regular use of AI tools and a practical understanding of what current AI technologies can and cannot do.
• Comfort operating in a fast-moving, early-stage environment where priorities may shift and solutions need to be developed quickly but thoughtfully.

Nice to have

• Experience in enterprise implementation, deployment, professional services, customer engineering, or technical consulting.
• Experience working with large enterprise clients in Singapore, especially across FSI, telco, insurance, aviation, or other complex industries.
• Startup or zero-to-one environment experience.

Key Responsibilities

Cloud Infrastructure & Automation

• Design, deploy, and maintain cloud environments on AWS or GCP.
• Develop and manage infrastructure using Infrastructure-as-Code tools such as Terraform or similar technologies.
• Implement secure networking architectures, including VPCs, private connectivity, VPNs, peering, and network segmentation.
• Establish scalable multi-environment and multi-account cloud strategies.

Container Platform & Kubernetes

• Build and manage Kubernetes environments for production workloads.
• Configure cluster security, RBAC, autoscaling, workload isolation, and governance controls.
• Create standardized deployment frameworks for microservices, backend services, and AI-related workloads.
• Support both real-time and batch processing environments.

CI/CD & Release Automation

• Design and optimize CI/CD pipelines to streamline software delivery.
• Implement automated testing, deployment validation, and release management processes.
• Support deployment strategies such as blue-green, canary, and phased rollouts.
• Improve developer productivity through automation and deployment standardization.

Observability & Site Reliability

• Implement monitoring, logging, tracing, and alerting solutions.
• Define service reliability metrics, performance objectives, and operational standards.
• Support incident response processes, root-cause analysis, and continuous service improvement.
• Develop operational runbooks and support on-call readiness.

Security & DevSecOps

• Strengthen cloud security through identity and access management best practices.
• Manage secrets, certificates, and sensitive configuration securely.
• Implement vulnerability scanning, dependency analysis, and container security controls.
• Enforce security policies through automation and governance frameworks.
• Support audit readiness and compliance requirements.

AI/ML Platform Support

• Collaborate with data science and machine learning teams to operationalize AI solutions.
• Support model deployment, inference services, batch processing, and ML infrastructure.
• Monitor performance, availability, and resource consumption of AI workloads.
• Contribute to platform capabilities that improve AI product scalability.

Cost Optimization

• Monitor cloud spending and resource utilization.
• Implement tagging, budgeting, and optimization initiatives.
• Drive efficiency improvements without compromising performance or reliability.

Developer Experience

• Build self-service infrastructure capabilities and reusable engineering templates.
• Improve internal tooling and automation workflows.
• Maintain clear technical documentation and operational guidelines.
• Help create a smooth developer experience across engineering teams.

Requirements

Essential Skills & Experience

• Minimum 4 years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or related infrastructure roles.
• Strong hands-on experience with AWS or Google Cloud Platform.
• Proven expertise with Infrastructure-as-Code tools, preferably Terraform.
• Solid Kubernetes administration and containerization experience (Docker, Helm, Kustomize, etc.).
• Strong knowledge of CI/CD pipelines and modern software delivery practices.
• Good understanding of Linux systems, networking, and automation scripting using Python and/or Bash.
• Experience implementing monitoring, logging, and observability solutions.
• Strong understanding of cloud security principles, IAM, secrets management, and infrastructure hardening.
• Ability to collaborate effectively with software engineers, product stakeholders, and technical leadership.
• Strong documentation and communication skills.

Preferred Qualifications

• Experience with GitOps practices and tools such as ArgoCD or Flux.
• Exposure to policy-as-code and infrastructure testing frameworks.
• Familiarity with data engineering or machine learning ecosystems.
• Experience working with distributed systems, streaming platforms, or large-scale data processing technologies.
• Knowledge of enterprise compliance, governance, and security review processes.
• Exposure to reliability engineering practices such as resilience testing or disaster recovery exercises.

Key Responsibilities

Product Design & Development

• Lead the mechanical design and development of new products and product enhancements.
• Create innovative concepts and translate them into detailed mechanical designs.
• Develop modular hardware architectures and reusable design solutions.
• Design complex mechanical systems, assemblies, and mechanisms while balancing performance, cost, manufacturability, and reliability.
• Convert product and customer requirements into practical engineering solutions.

Engineering Analysis & Validation

• Perform engineering calculations and technical analyses on components and assemblies.
• Identify technical risks early and develop effective mitigation plans.
• Develop and execute testing strategies, validation plans, and prototype evaluations to verify design performance.
• Ensure quality and reliability considerations are incorporated throughout the design process.

Project Execution

• Manage mechanical development schedules and deliverables for assigned projects.
• Support project planning activities and ensure designs are delivered on time and within budget.
• Collaborate with stakeholders to define product specifications and technical requirements.
• Drive continuous improvement initiatives and contribute to value engineering efforts.

Manufacturing & Production Support

• Work closely with manufacturing teams to support product industrialization and production readiness.
• Provide expertise in manufacturing processes including injection molding, machining, sheet metal fabrication, assembly, and related production methods.
• Troubleshoot manufacturing and product performance issues and implement design improvements when required.

Cross-Functional Collaboration

• Partner with Electrical, Firmware, Software, Manufacturing, Quality, and Product teams throughout the product development cycle.
• Participate in design reviews and contribute to multidisciplinary problem-solving efforts.
• Mentor and provide technical guidance to junior engineers where appropriate.

Requirements

Education & Experience

• Bachelor's degree in Mechanical Engineering or a related discipline.
• 8+ years of experience in mechanical product design and development.
• Proven experience taking products from concept and prototype stages through to mass production.

Technical Expertise

• Strong understanding of mechanical engineering principles and product development methodologies.
• Experience designing complex mechanisms such as:Gear trainsClutchesCamsLinkagesMotion-control systems
• Knowledge of electro-mechanical systems, including:MotorsSensorsPower transmission components
• Hands-on experience designing:Plastic componentsSheet metal partsDie-cast componentsRubber componentsMechanical assembliesElectro-mechanical assemblies
• Proficiency with SolidWorks and/or other 3D CAD tools.
• Familiarity with simulation and analysis tools (FEA preferred).
• Strong understanding of GD&T (Geometric Dimensioning & Tolerancing).

Preferred Qualifications

• Knowledge of Design of Experiments (DOE) and Six Sigma methodologies.
• Experience with:DFMEA (Design Failure Mode & Effects Analysis)Design for Manufacturing (DFM)Design for Assembly (DFA)Structured product evaluation and decision-making methodologies

About the Role

We are looking for an experienced mid-Senior Backend Developer responsible for building and scaling cloud-native backend services that power mission-critical AI products. This role is ideal for engineers who are comfortable designing cloud-oriented systems using modern engineering practices, and who have strong foundations in distributed systems and multi-threaded programming. You will work closely with product, frontend, and platform teams to deliver highly reliable, scalable, and secure backend systems in a fast-paced, agile environment.

Responsibilities

• Design and build cloud-native backend services and APIs that are scalable, secure, and production-ready.
• Develop and maintain backend components using C# / .NET (preferably .NET 8) following modern engineering standards.
• Contribute to system architecture for distributed systems, including service-to-service communication, resilience, and scalability patterns.
• Build systems that handle concurrency and multi-threading safely and efficiently (e.g., async patterns, thread safety, race conditions, performance tuning).

Requirements

• Min 3+ years of backend engineering experience with strong hands-on expertise in C# and .NET Core (V6 and above).
• Strong experience designing and building RESTful APIs and backend services.
• Proven ability to build cloud-oriented systems (AWS/Azure/GCP) using modern practices such as containerization, infrastructure awareness, and CI/CD.
• Solid understanding of distributed systems fundamentals and multi-threading / concurrency concepts.
• Strong SQL knowledge and experience with relational databases.

Overview

We are looking for a hands-on Senior Equipment Engineer to support equipment reliability, maintenance, and optimization within a high-tech manufacturing environment. This role plays a key part in ensuring tool uptime, process stability, and smooth production operations.

Responsibilities

• Perform troubleshooting and root cause analysis on equipment issues and process deviations
• Execute preventive and predictive maintenance to minimize downtime
• Monitor and improve equipment performance, uptime, and throughput
• Support yield improvement and process stability initiatives with cross-functional teams
• Ensure equipment readiness for new product introduction (NPI) and process qualification
• Maintain equipment documentation, logs, and spare parts inventory
• Ensure compliance with EHS, safety, and cleanroom standards
• Support audits and drive corrective actions where required

Requirements

• Bachelor’s degree in Mechanical / Electrical / Mechatronics Engineering or related field
• 5–10 years of experience in equipment engineering within semiconductor, substrate, or PCB manufacturing
• Hands-on experience with equipment such as:Wet benches, plating toolsCoaters / developersLamination presses, laser drills, vacuum ovens
• Strong experience in troubleshooting and root cause analysis (e.g., 5 Whys, Fishbone)
• Familiar with TPM, FMEA, and reliability engineering practices
• Knowledge of substrate technologies (e.g., SAP, ABF, Damascene) is an advantage