Principal Engineer, AI Cloud Software (AI)

Location: Singapore or Australia; the role is based in Sydney, New South Wales, Australia, and requires occasional overseas travel.

Company

hirify.global Technologies develops and operates energy-efficient AI infrastructure and hirify.global AI Cloud, a large-scale GPU cloud platform for training and deploying AI models.

What you will do

• Own the public API design, including resource models, contracts, versioning, compatibility, identity, and technical direction.
• Design and evolve the multi-region control plane for compute, virtual networking, storage, and Kubernetes resources at large scale.
• Build production software for long-running workflows, tenant isolation, federated identity, scoped credentials, approvals, audit trails, quotas, and usage metering.
• Keep the console, SDKs, CLI, and Terraform provider consistent with a single supported API contract.
• Set SLOs and error budgets, lead major incident response and post-mortems, and maintain security controls, patching, reliability, and cost discipline.
• Mentor engineers, lead design and code reviews, set engineering standards, conduct technical interviews, and shape the roadmap with product and platform teams.

Requirements

• Bachelor’s degree in computer science or a related technical field, or equivalent practical experience.
• 10+ years of software engineering experience, including at least 3 years at principal level or equivalent, with hands-on technical leadership across multiple teams.
• Experience designing and evolving public APIs used by external customers, including resource lifecycles, OpenAPI or gRPC contracts, versioning, backward compatibility, and a synchronized SDK, CLI, or Terraform provider.
• Experience running a multi-tenant control plane across multiple regions or data centres, serving thousands of tenants or millions of API requests per day with regional failure isolation.
• Experience implementing federated sign-on with OIDC or SAML, provisioning such as SCIM, role-based access, tenant isolation, secrets handling, and dependency patching under SOC 2 Type 2, ISO 27001, or an equivalent control set.
• Strong distributed-systems fundamentals, including consistency, idempotency, retries, backpressure, long-running workflows, and control-plane failure modes under heavy load.
• Production Kubernetes experience beyond deployment, including control-plane services using the Kubernetes API, custom resources, and controllers.
• Strong Go or Python skills, with infrastructure as code and CI/CD as part of daily work.
• Experience running a reliability programme involving SLOs, error budgets, change control, and incident reviews that changed the system.
• Clear written and verbal English communication for explaining technical problems, decisions, and trade-offs to engineers, executives, and customers; willingness to join the on-call rotation.

Nice to have

• Experience at an AI cloud or high-performance computing provider.
• Experience with customer-facing virtual networking or GPU node lifecycle APIs.
• Experience building usage metering, quotas, billing, hosted or virtual Kubernetes control planes, or tenant isolation for managed Kubernetes.
• Experience building customer-facing web applications with React or similar technology.
• Experience building agent-facing APIs, CLIs, MCP servers, or AI-assisted and agentic engineering workflows with security and governance controls.
• CKAD, CKA, or AWS Solutions Architect Professional certification.

Culture & Benefits

• The role operates in an AI infrastructure environment focused on efficiency, sustainability, and scalable cloud delivery.
• Occasional overseas travel is required.
• Participation in the on-call rotation is required for owned services.
• Engineering standards include secure AI-assisted development, review gates, automated architecture checks, and reliable operational practices.