Platform Engineer (Cloud & DevSecOps)

Salary: $7,000 – $8,500 per month

Platform Engineer (Cloud & DevSecOps)

Job Type: 1 year renewable contract

Job Requirement:

• A degree in Computer Science, Engineering, or a related discipline is preferred.

• 5 years in cloud engineering, platform engineering, DevOps, site reliability engineering, or software engineering, including hands-on experience building and operating cloud or platform services.

• Hands-on experience with Microsoft Azure or another major public cloud platform, including the operation of production cloud services.

• Hands-on experience with Kubernetes and containerised applications.

• Experience with infrastructure as code, automation, and Git-based workflows.

• Experience building and maintaining CI/CD pipelines and release automation.

• Strong programming skills and proficiency in Linux and shell scripting.

• Relevant cloud, certifications, Kubernetes, automation, security, or AI certifications (e.g. Microsoft Certified: Azure Administrator Associate or Certified Kubernetes Administrator) are an advantage.

Preferred Skills and Experience

• Strong experience with Microsoft Azure and managed Kubernetes services.

• Experience with CI/CD and platform tools, such as GitHub Actions, Jenkins, Sonatype Lifecycle and Repository Manager, Fortify, or SonarQube.

• Experience with infrastructure as code and configuration management tools, such as Terraform or Ansible.

• Experience with secrets management tools, such as HashiCorp Vault.

• Experience with GitOps tools, such as Argo CD, and cloud monitoring or observability platforms.

• Practical experience with AI in engineering work, such as AI coding assistants, AI agents, or the Model Context Protocol (MCP), or with running AI workloads on Azure, such as Azure OpenAI or Microsoft Foundry.

• Knowledge of AI security and governance risks, such as prompt injection, data leakage, and model supply chain risks, and related guidance such as the OWASP Top 10 for LLM Applications.

Job Summary

• Understands cloud platforms and the software delivery lifecycle, including where security, quality, and governance controls belong.

• Approaches work with an automation-first mindset and keeps cloud services and processes consistent and well documented.

• Writes structured, maintainable code and treats infrastructure and platform work as proper engineering.

• Takes ownership, follows work through to completion, and raises issues early.

• Keeps up with fast-moving AI developments and applies them pragmatically to improve how the team works.

Responsibilities:

Cloud Platform, Kubernetes & Operations

• Build and operate shared cloud platform services on Microsoft Azure, with a focus on reliability, scalability, security, and operational consistency.

• Run and evolve the cloud-hosted Kubernetes platform, including deployment workflows, platform services, monitoring, and security controls.

• Define service level objectives for platform services, build monitoring and alerting, respond to incidents, and lead blameless post-incident reviews.

Automation, Infrastructure as Code & CI/CD

• Automate cloud environments with infrastructure as code so that they are repeatable, consistent, and easier to operate.

• Design and improve cloud-native CI/CD pipeline templates that give application teams consistent and reliable delivery by default.

• Integrate security and quality controls, such as SAST and SCA, into cloud delivery workflows so that issues are identified early in the development lifecycle.

Security & Software Supply Chain

• Operate and improve the enterprise secrets management platform, including access policies, credential rotation, application integration, and self-service features.

• Manage the artifact repository platform so that software dependencies are governed, traceable, and checked for risk.

AI-Enabled Engineering

• Use AI to improve how the platform is built and run, such as automating routine operational tasks, analysing pipeline failures, and triaging security findings, with appropriate controls in place.

• Apply AI coding assistants and agents to accelerate the development of infrastructure as code, pipelines, and automation, and review generated code for quality and security before release.

• Deliver platform capabilities that allow application teams to run AI workloads securely, including access to large language model APIs, model hosting, and AI agent tooling such as MCP servers.

Platform Adoption & Collaboration

• Help application teams move to and adopt the cloud platform, including Kubernetes, CI/CD, secrets management, and other shared platform services.

• Treat the platform as a product: gather feedback from application teams, improve self-service and documentation, track adoption, and contribute to the cloud platform roadmap

Thanks, and Best Regards

Karanam Vijaya Kiran

(EA Registration no: R1443178)

Recruitment Manager

Hand Phone: +65 9473 3867

Helius Technologies Pte Ltd (EA Licence No: 11C3373)