Total 7 process development engineer job vacancies in Engineering category in Kuala Lumpur

Job Description

Responsibilities

• Major Fault Support & Review – Respond to Severity 1/2 incidents within 1 hour, log cases to Huawei TAC, lead troubleshooting, and conduct post event fault reviews.
• Operational Analysis – Deliver monthly reports covering cloud resource capacity, platform health, alarm analysis, and optimization recommendations.
• Risk Check – Perform quarterly in depth health checks (runtime status, capacity, configuration, warnings, version & license management) and provide rectification guidance.
• Basic & Advanced Cloud Service Version Upgrade – Lead upgrade solution design, pre upgrade checks, implementation, verification, and rollback for cloud platform and gPaaS/AI DaaS services
• Issue & Risk Management – Analyse issue trends, track unresolved escalated issues, and proactively identify and mitigate platform stability risks.
• Resource & Capacity Management – Analyse resource usage and provide scaling or reconstruction recommendations.
• Change Implementation – Implement configuration changes (including after hours support up to 8 hours/week as needed), obtain customer authorization, and perform rollback if required.
• Urgent Recovery & Troubleshooting – Assist TAC in emergency fault recovery, common issue resolution, and rapid service restoration.
• Routine PMI & Monitoring – Perform routine product inspections, monitor alarms via ManageOne/eSight, and ensure platform health

Job Requirements:

• Bachelor/Master of computer science engineering or related majors, with over 3 years O&M experience, including hands on work with cloud platforms (public/private cloud) or general IT (networks, OS, databases, middleware, basic IT components).
• Familiar with HCS deployment, tenant O&M processes (backup management, resource inspection, requirement management, risk management, asset management, expense analysis, monitoring & alarming.
• Strong foundational knowledge of datacom principles; familiar with TCP/IP, standard IP networking, and hybrid cloud networking; able to independently resolve basic datacom issues; proficient in physical network technologies and architectures.
• Strong capability to identify and demarcate cloud problems, lead problem closure, and drive backend improvements.
• Excellent customer service awareness and communication skills; able to work with multinational teams
• Attention to detail and strong execution capabilities

Preferred Qualifications:

• Experience maintaining or optimising large scale data centre network services.
• Experience with SDN delivery and maintenance.
• Familiarity with chaos engineering, fault drills, stress tests, and architecture optimisation.
• Experience in multinational team management (at least 2 years).

Apply Link: https://jobs.persolmalaysia.com/detail/39051?apply_id=39051&utm_source=jobstore&utm_medium=sponsored

Contact Email: jiahui.ang@persolapac.com

Perks & Benefits

• Personal leave
• Open culture
• Personal development opportunities

• Candidates must posses a Degree in Mechanical Engineering .

• Minimum 4-5 years working experience in HVAC / ACMV.

• Able to communicate well at all levels, both verbally and in writing.

• Possess good working attitude, initiative and self motivation to perform.

• Documentation Management.

Perks & Benefits

• Medical Benefit
• Pantry and Resting Area For Staff To Recharge
• Promotion Based On Performance
• Regular team activities
• Personal leave
• Personal development opportunities

Role Summary

Build and maintain internal automations, AI assistants and AI-powered marketing tools that increase speed, consistency, and performance in day-to-day execution. You’ll use a mix of low-code (e.g. n8n) and custom code, working closely with marketing, sales and other departments.

Importantly, you are someone who is passionate about what's possible with AI and eager to push the boundaries of what we can build internally. You should be experimenting with projects like OpenClaw and have your opinions on what are the best ways to build AI assistants to improve productivity.

KEY RESPONSIBILITIES

• Build automations: Use a combination of low code and custom code to build automations that dramatically improve productivity. Prior experience building production-grade automations is highly valued.
• AI Agent Development: Design and deploy production-grade AI agents, and understand requirements and tradeoffs for non-trivial projects (e.g. evaluation, self-learning, cost)
• AI Sales/Marketing Tools: Build AI-assisted workflows to help sales & marketing drive demand-gen. Experience using AI to generate TikTok/short-formvideo ad assets is highly valued.
• Process Automation: Map workflows, spot inefficiencies, and automate repeatable processes

• Builder mentality: Proactive, takes ownership, and not afraid of big goals and fast iteration
• Prior experience or willingness to learn how to create AI video pipelines
• Hands-on experience with LLM APIs and prompt engineering, and experience building or experimenting with AI agents or multi-step reasoning pipelines
• Coding ability: Proficient in Python for scripting, API integrations, and automation logic. Able to write clean, working code independently
• Clear communicator who can work with non-technical stakeholders.

What You’ll Do 

• Reverse Engineering & Decompilation: 
  Analyze web and mobile applications (APK/IPA) to uncover hidden mechanisms. Disassemble code to understand its inner workings, with a focus on cryptographic functions that secure our systems. 

• Overcoming Anti‑Bot Mechanisms: 
  Evaluate and bypass advanced security protocols such as TLS, HTTP/2, HTTP/3, WebSockets, DoH, and session management. Identify vulnerabilities to enhance our data extraction methods. 

• Developing Custom Tools: 
  Build robust Python scripts and frameworks that automate bypass procedures and dynamically adjust security measures—whether by modifying TLS stacks or patching JavaScript on the fly. 

• Implementing Stealthy Scraping Techniques: 
  Engineer sophisticated methods—such as browser patching, headless browser evasion, proxy tunneling, and human‑behavior emulation—to keep our operations discreet. 

• Continuous Innovation: 
  Regularly test, disrupt, and improve our tools to stay ahead of ever‑evolving defenses. 

Senior / Lead DevOps Engineer

Why You Should Apply
- Varied and strategic role across CI/CD, Infrastructure-as-Code (IaC), and Cloud Automation, reporting directly to the Head of Engineering.
- Lead all DevOps initiatives and set the foundations for CI/CD, automation, and shift-left practices.
- Clear 6-12 month objective to standardise CI/CD and reduce manual release and build processes, with full leadership support and resources.
- Opportunity to join a stable global financial services company (non-bank) that has established a regulated product suite in Malaysia over the past 5 years.

What You Will Do
- Lead the design and implementation of CI/CD pipelines, reusable pipeline architecture, quality gates, branching governance, automation testing, and release discipline.
- Establish CI foundations across repositories, build validation, early defect detection, and Git workflow standards.
- Drive Continuous Delivery and Deployment Automation, improve rollback strategies, release traceability, and reduce manual intervention.
- Implement Infrastructure-as-Code practices and cloud automation initiatives.
- Enhance deployment strategies, including blue-green and canary deployments.

What You Will Need
- Minimum 6 years of hands-on DevOps experience with AWS or similar platforms (Azure, GCP).
- Relevant experience as a DevOps engineer, cloud engineer, platform engineer, build & release engineer, or SRE.
- Ability to work independently and hands-on, driving digital transformation without reliance on a large team or strict SOPs.
- Experience in fintech, tech companies, product companies, or digital transformation teams within enterprise/MNC environments.
- Strong CI/CD transformation experience (Git-based CI, Jenkins, etc.).
- Hands-on experience with containerization and Infrastructure-as-Code.

About the Company & Team
- Malaysian team and product suite are less than 5 years old, part of a globally established fintech and financial services company operating in 15 countries.
- Regulated under Bank Negara Malaysia, ensuring high regulation and financial security.
- All products are built in-house, enabling long-term initiatives with internal technical capability.
- Provides end-to-end solutions across front, middle, and back office functions, serving both retail and institutional customers under its own brand and a white-label B2B product.
- Hybrid work arrangement, based in central Kuala Lumpur.

How to Apply
- Click the “apply” button. You may submit your CV or LinkedIn profile—whatever you prefer.
- The recruiter is happy to share more information with you before you proceed.
- Every applicant or enquiry will receive a reply.

Note
- Employment passes, work visas, or relocation support are not available.
- Only candidates with work rights in Malaysia will be considered.

As an Applications Intern, you will gain hands-on experience in supporting and improving business applications used across the organisation. You will work with systems such as Power BI, Business Central, LS Retail, E-Commerce, and other key business platforms, while learning how enterprise applications are managed in a real business environment.

Working closely with the Applications and Operations team, you will support daily operations, assist in projects and testing activities, and contribute to documentation and process improvements.

Your responsibilities will include:

Assisting with Level 2 support activities through the service desk

Supporting the team in maintaining and enhancing business applications and reporting solutions

Helping with daily backend maintenance and job monitoring tasks

Supporting User Acceptance Testing (UAT) and test preparation activities

Supporting application setup and handover activities for end-users

Preparing and updating technical documentation, process guides, and training materials

Job Summary:
We are seeking a skilled ML Ops / AI Integration Engineer to build, integrate, and manage Generative AI and Agentic AI solutions within enterprise environments. The ideal candidate will work closely with data scientists, architects, and DevOps teams to design, deploy, and optimize AI pipelines, ensuring scalable, secure, and reliable AI systems. This role focuses on automation, cloud integration, and production deployment of AI models.

Key Responsibilities

• Develop and maintain automation scripts using Linux shell scripting, Python, and other automation tools.
• Ensure seamless deployment and integration between cloud and on-premise environments (AWS).
• Integrate AI and machine learning models into production environments using containerized platforms such as OpenShift.
• Implement and maintain network security protocols to protect AI systems and data pipelines.
• Collaborate with data scientists, DevOps engineers, and architects to translate AI workflows into scalable engineering solutions.
• Monitor, maintain, and optimize system performance, reliability, and scalability.
• Support and maintain CI/CD pipelines for AI model deployment and continuous updates.
• Implement logging, monitoring, and observability frameworks to ensure system stability.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 4+ years of experience in Machine Learning Engineering, MLOps, or AI system integration.
• Strong experience with Bash and Unix/Linux command-line tools.
• Hands-on experience with OpenShift, Docker, and Kubernetes.
• Experience with cloud platforms such as AWS.
• Knowledge of network security and compliance practices related to AI systems.
• Experience with API integrations and microservices architecture.
• Proficiency in Python for automation and machine learning related tasks.
• Experience with workflow orchestration tools such as Ctrl-M.
• Good knowledge of logging and monitoring tools such as Splunk and Geneos.
• Experience with observability frameworks such as Langfuse, Elastic Stack, Grafana, and OpenTelemetry.
• Understanding of Generative AI concepts such as prompt engineering, RAG pipelines, and Agentic AI frameworks.