Total 4,947 operations engineer job vacancies in Engineering category in Hong Kong

Responsibilities:

• Design, development, testing and support of firmware/embedded software applications for microcontroller based wireless systems.
• Develop software communication protocols for wireless communication systems
• Drive technology/development projects in all phrases from specification to release.
• Read or understand electronics schematic and system design.
• Work closely with cross functional teams to ensure project delivery on time.
• Define and create product software specification including software architecture, feature descriptions and applications notes of the system
• Research technical issues and/or opportunities and provide recommendations.
• Participate in ad hoc software projects and assignments as required.

Requirement:

• Degree in Electronic/Electrical/Computer Engineering/Computer Science, Software Engineering or related fields.
• Minimum 3-5 years of experience in real time embedded system
• Must process strong knowledge of C/C++ language
• Experience with Arm, Cortex based microcontroller is required
• Strong Knowledge of the communication transport protocol like I2C, SPI, UART and USB
• Understanding of the Bluetooth protocol and stack is a plus.
• Familiarity with DSP programming is an added advantage
• Excellent teamwork skills, flexibility, and ability to handle multiple tasks.
• Able to manage one's own time efficiently

Overview

This role is responsible for building, maintaining, and securing the platform infrastructure that enables data ingestion from multiple enterprise and government data sources.

The successful candidate will ensure reliable, scalable, and secure connectivity between external systems and the platform, supporting the delivery of actionable cyber asset intelligence and vulnerability management capabilities.

The role plays a key role in agency onboarding, platform integration, infrastructure operations, and ongoing platform reliability.

Responsibilities

Agency Technical Onboarding

• Prepare technical onboarding requirements, including service accounts, API credentials, permissions, and network connectivity requirements.
• Provide technical guidance on integration prerequisites and credential provisioning.
• Act as the primary technical contact during onboarding and integration activities.
• Troubleshoot connectivity, authentication, and access-related issues.

Platform Integration & Connector Management

• Configure and deploy data connectors and integrations.
• Monitor data ingestion pipelines and resolve failures or data quality issues.
• Maintain and update connector configurations as requirements evolve.
• Collaborate with Data Engineers to ensure successful data ingestion and downstream processing.

Infrastructure Operations

• Provision, maintain, patch, and scale platform infrastructure.
• Manage network connectivity, including firewalls, VPNs, proxies, and related configurations.
• Ensure compliance with security standards and operational policies.
• Monitor system performance, availability, and capacity.
• Respond to incidents, outages, and operational issues.

Platform Lifecycle & Change Management

• Support platform setup, environment provisioning, and operational readiness activities.
• Contribute to platform architecture and technical design decisions.
• Develop and maintain operational runbooks, technical documentation, and standard operating procedures.

Requirements

Essential Skills & Experience

• Minimum 3 - 7 years of experience in Infrastructure Engineering, Platform Engineering, or Systems Administration.
• Experience working with data integration platforms, APIs, connectors, or ETL/ELT solutions.
• Strong understanding of networking concepts, including firewalls, DNS, proxies, and VPNs.
• Experience managing service accounts, API credentials, certificates, and access controls.
• Familiarity with Infrastructure as Code (IaC) tools such as Terraform or Ansible.
• Strong troubleshooting skills across network, authentication, and application layers.

Preferred Skills & Experience

• Experience with cyber asset management or IT asset platforms. (e.g., Axonius, Armis,
  ServiceNow CMDB, Qualys)
• Understanding of cybersecurity concepts such as attack surface management, vulnerability management, and asset discovery.
• Familiarity with cloud environments and shared enterprise services.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, or ELK.
• Experience working in cross-functional teams alongside Data Engineers, Business Analysts, and other technical stakeholders.

Key Competencies

• Technical Problem Solving: Ability to diagnose and resolve complex infrastructure and integration challenges effectively.
• Security Mindset: Applies secure-by-design principles, least-privilege access, and security best practices.
• Operational Excellence: Maintains reliable and scalable systems through monitoring, documentation, and incident management.
• Collaboration & Communication: Works effectively with technical and non-technical stakeholders to deliver successful outcomes.
• Adaptability: Comfortable operating across diverse environments, technologies, and stakeholder groups.

Key Responsibilities

• Design, develop, and maintain applications using C#, .NET Framework (.NET 4.5+), frontend frameworks, and SQL Server in a production-critical environment.
• Take end-to-end ownership of assigned modules, including development, enhancements, and defect resolution.
• Provide L2/L3 production support, including incident troubleshooting, root cause analysis (RCA), and permanent remediation.
• Manage and prioritise high-volume work queues / operations tasks, ensuring SLA compliance.
• Drive code quality and maintainability, including refactoring and reduction of technical debt.
• Collaborate with cross-functional teams to resolve integration and system dependencies.
• Review and approve technical designs, code, and documentation, ensuring adherence to standards.
• Proactively identify risks and recommend improvements to enhance system performance, stability, and observability.
• Utilise monitoring and logging tools to detect issues early, analyse system behaviour, and improve reliability.

Mandatory Requirements 

• 6–8+ years of hands-on experience in .NET development within enterprise systems.
• Strong backend expertise in:C#, ASP.NET / MVC (mandatory)SQL Server /Oracle DB (query optimization, indexing, performance tuning)
• Frontend experience in:AngularJS OR ReactJS (mandatory at least one, hands-on)Exposure to modern frontend frameworks is an advantage
• Proven experience in:Application Maintenance & Support (AMS) / production support environmentsIncident management, RCA, and issue ownership
• Mandatory experience in Public Sector / Government projects
• Experience in domain systems such as healthcare, insurance, or other large-scale transactional systems is strongly preferred
• Strong understanding of:Multi-tier architecture and system integrationsSecure coding practices
• Hands-on experience with:Version control (Git / TFS)Structured release/delivery processes (CI/CD exposure preferred)Monitoring and observability tools (e.g., logging, alerting, performance monitoring)
• Strong problem-solving mindset with excellent investigation and troubleshooting skills, with the ability to analyse complex issues, identify root causes, and implement effective resolutions in production environments
• Proven ability to operate effectively in SLA-driven environments
• Familiarity with AWS or Azure cloud environments
• Able to join within short notice (preferred: ≤ 1 month)

Advantageous Skills

• Experience in large-scale, high-transaction systems
• Exposure to microservices or API-driven architectures
• Experience with advanced monitoring, logging, and performance tuning tools

Behavioural Expectations

• Strong ownership and accountability mindset
• Ability to work independently and manage priorities effectively
• Proactive communicator with stakeholders and project managers
• Capable of guiding junior developers and enforcing best practices
• Comfortable operating in a fast-paced AMS/support environment
• Demonstrates a systematic and analytical approach to problem-solving under pressure

Key Responsibilities

• Analyse and optimize manufacturing processes to improve productivity, efficiency and product quality.
• Partner with Engineering, Production, Materials, Systems and Maintenance teams to resolve manufacturing issues and improve operational performance.
• Support the implementation of new manufacturing processes, production plans and engineering projects.
• Drive continuous improvement initiatives across manufacturing operations.
• Monitor and improve manufacturing KPIs, including:QualityProduction volumeProcess capacityManufacturing efficiencyProduct integrityProduct certificationCostInventory performance
• Prepare operational reports and present findings to management.
• Support cycle time reduction and capacity improvement initiatives.
• Collaborate with cross-functional stakeholders to achieve manufacturing and business objectives.
• Ensure compliance with company quality standards and manufacturing procedures.

Requirements

• Diploma or Degree in Mechanical, Manufacturing, Industrial or related Engineering discipline.
• At least 3 years of relevant Industrial Engineering or Manufacturing Engineering experience.
• Prior experience in Server Manufacturing, Electronics Manufacturing, Semiconductor or High Precision Manufacturing will be advantageous.
• Knowledge of manufacturing process optimization, production planning and continuous improvement methodologies.
• Strong analytical, problem-solving and communication skills.
• Able to work independently while collaborating effectively across multiple departments.
• Proficient in Microsoft Excel and manufacturing data analysis.

What's on Offer

• Competitive salary package
• Permanent opportunity with an established MNC
• Comprehensive employee benefits
• Stable business with strong growth
• Structured training and career progression
• Collaborative and professional working environment
• Convenient Tampines location

Applicants who possess relevant experience for the above responsibilities are most welcome to apply. If you do not possess the above experience, your application will still be considered on individual merits and you may be contacted for other opportunities. 

By submitting your personal data and/or resume, you give consent to collection, use and disclosure of your personal data and/or resume by the company (or its agent) for the purpose of the processing and administration by the company relating to this job application. 

**We regret to inform that only shortlisted candidates would be notified

Interested applicants may click APPLY NOW!

Talentvis Singapore Pte Ltd | EA License No: 04C3537
EA Personnel Name: Ong Hui Shan (Gwen) | EA Personnel No: R1767800

Our esteemed client in the IT industry is seeking a Full Stack Engineer (React/ Node.js) to join their dynamic team:

• Employment Type: 1-year renewable contract
• Position: Full Stack Engineer (React / Node.js)
• Location: Central
• Working Hours: Monday to Friday, Office Hours
• Salary Package: Basic + Bonus + Medical Benefits

Job Responsibilities:

• Provide technical oversight for the web portal post-migration, troubleshooting issues related to UI/UX rendering, CMS templates, API integrations, and data ingestion to ensure a smooth transition into steady-state operations.
• Develop and implement new front-end components using React/Next.js and back-end logic using Node.js/TypeScript. This includes building complex data checkers, search tools, and personalized user features.
• Design and maintain secure integrations with internal back-end systems, external datasets, and secure file transfer protocols, ensuring the robust handling of API keys and tokens.
• Configure modules, workflows, and metadata within a headless CMS environment (Directus or similar), ensuring the platform remains intuitive for content and product teams.
• Lead UAT defect resolution and implement automated testing suites. Ensure all code meets strict accessibility (WCAG), performance, and security standards (including VAPT remediation).
• Actively participate in agile ceremonies (sprint planning, retrospectives) and collaborate with designers, product owners, and QA teams using GitLab for version control and CI/CD.
• Maintain comprehensive technical documentation, including system architecture updates and release notes.

Job Requirements:

• Strong hands-on experience with Node.js, TypeScript, React, and Next.js, with the ability to build and maintain full stack web applications.
• Experience working with Directus CMS or similar headless CMS platforms, including configuration of modules, workflows, and content components.
• Good understanding of REST APIs, JSON, OAuth2, and API security, with experience integrating internal and external systems.
• Familiarity with GitLab, CI/CD pipelines, DevSecOps practices, Docker, and containerised deployments.
• Knowledge of cloud and web infrastructure, preferably AWS services such as EC2, S3, CDN, and Load Balancers.
• Experience implementing automated testing (unit, integration, end-to-end), code quality checks, accessibility compliance (WCAG), and performance optimisation.
• Strong troubleshooting and debugging skills across frontend, backend, and cloud environments, with the ability to support production systems effectively.

Ready to apply? Here’s how: 

• Click the APPLY button, or 
• Email your resume (in MS Word or PDF format) to adelin@intuitrecruitment.com. Include the job title in your email subject line for prompt processing. 

Only shortlisted candidates will be notified. 

By submitting your application, you consent to the collection and use of your personal data under Personal Data Protection Act (PDPA). 

Adelin Chong | EA Personnel Reg No.: R1875641 

Intuit Recruitment Pte Ltd | EA License No.: 25C2793 

About the Role

We are looking for exceptional AI Engineers to build the next generation of AI infrastructure and Machine Learning Systems(MLSys).

This role focuses on large-scale system infrastructure rather than model research. You will work on the core foundations that power large-scale AI training and inference systems, including Kubernetes cluster management, RDMA networking, unified KV Cache architecture, observability platforms, distributed systems, GPU orchestration, and CUDA kernel optimisation.

You will collaborate closely with AI researchers, infrastructure architects, networking engineers, and platform teams to maximize the efficiency, scalability, and reliability of AI systems.

Key Responsibilities

AI Infrastructure & Kubernetes

• Design, deploy, and operate large-scale Kubernetes-based AI infrastructure.
• Develop cluster governance frameworks, scheduling policies, resource isolation, and multi-tenancy capabilities.
• Build and optimize GPU orchestration platforms using Kubernetes, Slurm, Volcano, Kueue, Ray, and related technologies.
• Improve cluster utilization, reliability, elasticity, and operational efficiency.

RDMA & High-Performance Networking

• Design and optimize RDMA, InfiniBand, RoCE, and high-speed Ethernet fabrics for distributed AI workloads.
• Optimize GPU-to-GPU and GPU-to-NIC communication paths.
• Improve distributed communication efficiency for large-scale training and inference.
• Analyze and eliminate networking bottlenecks across AI clusters.

Unified KV Cache & Distributed Memory Systems

• Design and implement unified KV Cache architecture across:
• GPU HBM
• CPU Memory
• RDMA-accessible Memory
• NVMe SSD
• Distributed Storage
• Develop efficient KV Cache sharing, migration, offloading, and scheduling mechanisms.
• Optimize latency and throughput for large-scale inference systems.

CUDA & System Performance Optimisation

• Develop and optimize CUDA kernels for training and inference workloads.
• Profile and optimize GPU compute, memory, communication, and scheduling efficiency.
• Contribute to low-level optimization of AI frameworks and inference engines.
• Work on technologies such as FlashAttention, TensorRT, Triton, NCCL, CUTLASS, and custom operators.

Observability & Reliability

• Build end-to-end observability platforms for AI infrastructure.
• Design monitoring, logging, tracing, alerting, and troubleshooting frameworks.
• Develop performance dashboards and SLO-driven operational systems.
• Improve maintainability, debuggability, and operational excellence of AI platforms.

Automation & Platform Engineering

• Build automation tools for deployment, provisioning, monitoring, and operations.
• Develop Infrastructure-as-Code (IaC) solutions using Terraform, Ansible, and related tools.
• Build CI/CD pipelines and engineering productivity platforms.
• Improve platform scalability and operational efficiency.

Required Qualifications

Education

• Bachelor's degree or above in Computer Science, Software Engineering, Electrical Engineering, or related fields.

Technical Skills

• Strong software engineering and programming skills.
• Excellent system design capability and strong engineering craftsmanship.
• Strong coding standards and code quality awareness.
• Strong sense of ownership, accountability, and execution.

System Fundamentals

Strong understanding of:

• Operating Systems
• Computer Networks
• Distributed Systems
• Data Structures and Algorithms
• Linux Internals

Programming Languages

Proficiency in one or more of:

• C++
• Go
• Python
• Rust

AI Infrastructure Experience

Hands-on experience in one or more of:

• Kubernetes
• GPU Infrastructure
• Distributed Systems
• AI Infrastructure
• HPC (High Performance Computing)
• Cloud-Native Platforms

Networking Experience

Experience with:

• RDMA
• InfiniBand
• RoCE/RoCEv2
• GPUDirect
• NCCL
• UCX
• High-Speed Ethernet

GPU & Performance Engineering

Experience with:

• CUDA
• GPU Performance Optimization
• Multi-GPU Systems
• Distributed Training
• Distributed Inference

Preferred Qualifications

• Experience building large-scale AI training or inference clusters.
• Experience with vLLM, SGLang, TensorRT-LLM, Triton, DeepSpeed, Megatron-LM, Ray, or similar frameworks.
• Experience with unified KV Cache systems, memory hierarchy optimisation, or distributed storage systems.
• Experience with Kubernetes GPU Operator and NVIDIA NetworkOperator.
• Experience with Prometheus, Grafana, Loki, OpenTelemetry, and observability platforms.
• Experience contributing to open-source projects such as: vLLM, FlashAttention, CUTLASS, TVM, MLIR, Triton, Kubernetes, NCCL
• Experience working across AI Infrastructure, HPC, Networking, and Silicon Systems is highly desirable.