DevOps & Edge Integration Engineer

Red Dot AI; Singapore; Hybrid; SGD 70,000 - 110,000; Full time

Job summary

Red Dot AI is a Singapore-based deep-tech company delivering cloud and on-site integration for data center operations. The role bridges cloud operations, offline deployment, and industrial protocol integration, leveraging AI tools to improve efficiency and reliability across restricted networks.

You will work across DevOps, edge deployments and automation, interfacing with customers and vendors to ensure smooth operation of systems in cloud and on-site environments.

Qualifications

• 2–6 years of experience in DevOps, cloud platforms, system integration or deployment engineering.
• Proficiency in Linux, Docker, shell or Python, CI/CD, logging and monitoring.
• Ability to deploy and operate Kubernetes in offline or restricted networks.
• Familiarity with Azure, GCP or Alibaba Cloud security basics.
• Strong English communication with customers and global teams.
• Interest in AI coding tools and automation; practical scripting.
• Proficiency in creating deployment guides and incident reports.

Responsibilities

• Cloud Platform & DevOps Operations: Build and maintain Azure/GCP, Docker/Kubernetes and other cloud and internal environments.
• On-site Deployment & Edge Integration: Deploy in restricted/offline environments, manage upgrades and rollbacks.
• Automation & AI-Assisted Tools: Write scripts for deployment, monitoring, analytics; use AI coding tools to boost productivity.
• Cross-Team Collaboration: Coordinate with backend, data science, and customer teams; document deployments and processes.

Skills

DevOps experience

Linux

Docker

Python

CI/CD

Monitoring

Tools

Terraform

Ansible

Helm

GitOps

Job description

Red Dot AI is a Singapore-based deep-tech company incubated by Nanyang Technological University and certified by the Infocomm Media Development Authority (IMDA). We leverage physics-based digital twin technology, AI agents and real-time infrastructure intelligence to convert complex data center operations into actionable decisions, helping customers optimise computation, energy consumption, cooling and operations.

Position Summary

We are seeking an engineer who bridges cloud operations and on-site integration. You will be a key member working across DevOps, offline deployment, industrial protocol integration and engineering automation. You will leverage AI tools to enhance productivity and communicate effectively with customers and vendors to ensure reliable operation of our systems in both cloud environments and restricted networks.

Responsibilities

• Cloud Platform & DevOps Operations: Build and maintain Azure/GCP, Docker/Kubernetes and other cloud and internal environments to support development, testing and demonstrations. Manage CI/CD pipelines, image repositories, security configurations and monitoring to ensure stable delivery of cloud products.
• On-site Deployment & Edge Integration: Implement project deployments in restricted or offline environments, handle version upgrades, rollbacks and troubleshooting. Interface with systems such as BMS/DCIM and other on-site systems and IoT gateways, support data ingestion via protocols including Modbus, OPC, MQTT and RESTful APIs; develop data ingestion scripts and monitor data quality and link stability.
• Automation & AI-Assisted Tools: Write and maintain scripts for deployment, monitoring, log analysis and validation. Use AI coding tools such as Claude Code and Codex to improve efficiency. Design lightweight test or validation harnesses to enhance the reliability of packages and data interfaces.
• Cross-Team Collaboration & Business Learning: Collaborate with backend developers, data scientists and customer project teams to coordinate deployment plans and produce technical documentation. Quickly learn data center and HVAC fundamentals to understand customer scenarios and optimize operational strategies. Excellent communication skills with customers and vendors are essential for aligning requirements and driving success across teams.

Required Qualifications

• 2–6 years of experience in DevOps, cloud platforms, system integration or deployment engineering; proficient in Linux, Docker, shell or Python, CI/CD, logging and monitoring.
• Ability to independently deploy and operate Kubernetes or other container orchestration environments, and adapt to offline or restricted network settings.
• Familiarity with compute, network and storage services and basic security management on cloud providers such as Azure, GCP or Alibaba Cloud.
• Strong communication skills and fluency in English for working with customers, vendors and global teams.
• Interest in using AI coding tools to improve productivity and a passion for automation; capable of writing practical scripts and internal tools.
• Proficiency in writing clear documentation, including deployment guides, incident reports and client updates.

Preferred Qualifications

• Experience integrating industrial communication protocols such as Modbus, OPC UA, MQTT, RESTful APIs or SNMP.
• Familiarity with infrastructure-as-code tools like Terraform, Ansible, Helm or GitOps.
• Experience working on energy efficiency optimization, cooling system optimization or data center operations projects.
• Experience with offline deployments, private implementations or air‑gapped environment maintenance.
• Familiarity with BMS/DCIM or industrial IoT platforms.

The ideal candidate combines system operations and data integration skills. You are comfortable building and maintaining cloud environments and supporting on-site deployments. You communicate effectively with customers and vendors, take initiative to learn industrial protocols and domain knowledge. You are proficient in leveraging AI tools and technologies and are passionate about emerging technology and innovation. You enjoy using code to solve repetitive problems and collaborate well across functions.