[Hiring] Cloud Service Security Platform DevOps & Maintenance @Bitdeer Technologies Group

Role Description

You are the paved road for every AI product we ship — the CI/CD, IDP, and MLOps substrate that lets model teams deploy without opening a ticket. This is an entry-to-mid level role.

Bitdeer is building an AI-operated GPU cloud, and the AI Cloud team ships the products on top of it. As Cloud Senior DevOps Engineer you build the paved road those products travel down:

• CI/CD, infrastructure-as-code, MLOps pipelines, and the Internal Developer Platform that lets model, data-science, and product teams deploy at speed without stepping around governance.
• You are the bridge between research and production, and the operator of the platform substrate the AIOps team plugs into.

Qualifications

• Bachelor's degree or above in Computer Science, Engineering, or a related technical field.
• 5+ years of hands-on experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles.
• Expert-level knowledge of Linux operating systems and core networking principles (TCP/IP, DNS, HTTP, Load Balancing, VPCs).
• Deep mastery of Docker and Kubernetes orchestration.
• Proven proficiency in designing and managing infrastructure on major Public or Hybrid Cloud platforms (e.g., AWS, GCP, Azure, Alibaba Cloud).
• Strong coding and scripting capabilities in at least one major language (Go, Python, Shell, etc.).
• Systematic and practical understanding of CI/CD methodologies, Infrastructure as Code (IaC), Observability paradigms, and Site Reliability Engineering (SRE) principles.
• Exceptional problem-solving abilities, sharp technical judgment, and excellent cross-team communication skills.

Requirements

• Design, implement, and maintain end-to-end CI/CD pipelines for both software applications and machine learning models.
• Automate build, test, deployment, and rollback processes to ensure seamless transitions from innovation to production.
• Build, optimize, and scale cloud-native infrastructure using Kubernetes (K8s) and Docker.
• Manage and provision specialized computing resources (e.g., GPU clusters) to support high-performance AI workloads and model inferencing.
• Take ownership of high-availability design in production environments.
• Implement disaster recovery (DR) strategies, self-healing mechanisms, capacity planning, and performance tuning to meet stringent business SLAs.
• Champion IaC practices utilizing tools such as Terraform, Ansible, and Helm.
• Architect and refine comprehensive monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK/EFK stack).
• Build the paved road that lets product, model, and data-science teams deploy without opening a ticket.
• Work closely with R&D, Data Science, Security, and Business teams to streamline workflows.
• Establish and enforce system stability and security standards.
• Act as the technical lead during complex system anomalies and major incidents.

Preferred Qualifications (Plus)

• Familiarity with MLOps practices, model serving/inferencing frameworks (e.g., vLLM, TGI, Triton Inference Server).
• Proven track record working with large-scale distributed systems or high-concurrency environments.
• Hands-on experience in designing and building Internal Developer Platforms (IDP).
• Deep familiarity with Zero Trust architecture and automated security testing (DevSecOps).
• Prior experience acting as a Technical Lead, mentoring junior engineers, or managing DevOps teams.
• You see incidents, tickets, and manual runbooks as source material for the next automation.
• You think in golden paths and defaults, not policies.

Benefits

• Equal employment opportunities in accordance with country, state, and local laws.
• No discrimination against employees or applicants based on various conditions.