AI Cloud Senior DevOps Engineer

Cloud Senior Dev Ops Engineer

Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure. Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.

We are seeking a highly skilled and motivated Cloud Senior Dev Ops Engineer to join our AI Cloud team. In this high-impact role, you will be the backbone of our deployment and infrastructure operations, ensuring that our AI-powered products and platforms are delivered with speed, security, and exceptional reliability. You will act as a crucial bridge between our research/development teams and real-world deployment, driving automation, optimizing cloud-native architectures, and establishing best practices for MLOps and traditional Dev Ops workflows.

Key Responsibilities:

• CI/CD & MLOps Pipeline Management:
  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.
• Cloud-Native & AI Infrastructure:
  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.
• High Availability Architecture:
  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.
• Infrastructure as Code (IaC):
  Champion IaC practices utilizing tools such as Terraform, Ansible, and Helm to achieve fully automated, reproducible, and auditable infrastructure provisioning across multiple cloud environments.
• Observability & Monitoring:
  Architect and refine comprehensive monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK/EFK stack) to provide deep visibility into system health, application performance, and AI model metrics.
• Cross-functional Collaboration:
  
  Work closely with R&D, Data Science, Security, and Business teams to streamline workflows, eliminate bottlenecks, and continuously elevate engineering efficiency through Internal Developer Platforms (IDP) and Platform Engineering initiatives.
• Governance, Security & Compliance:
  Establish and enforce robust system stability and security standards. Manage release workflows, implement Zero Trust access controls, oversee secrets management, and ensure compliance with industry frameworks (e.g., SOC2, ISO
  27001).
• Incident Management & Resolution:
  Act as the technical lead during complex system anomalies and major incidents. Spearhead rapid troubleshooting, conduct thorough root cause analysis (RCA), and implement preventative remediation plans.

Basic Qualifications:

• Experience &
  
  Education:
  
  Bachelor's degree or above in Computer Science, Engineering, or a related technical field, with 5+ years of hands-on experience in Dev Ops, Site Reliability Engineering (SRE), or Cloud Infrastructure roles.
• Networking & OS:
  Expert-level knowledge of Linux operating systems and core networking principles (TCP/IP, DNS, HTTP, Load Balancing, VPCs).
• Containerization & Orchestration:
  Deep mastery of Docker and Kubernetes orchestration, including a thorough understanding of underlying principles, cluster management, and production-level best practices.
• Cloud Platforms:
  Proven proficiency in designing and managing infrastructure on major Public or Hybrid Cloud platforms (e.g., AWS, GCP, Azure, Alibaba Cloud), including multi-cloud and hybrid-cloud strategies.
• Programming
  
  Skills:
  
  Strong coding and scripting capabilities in at least one major language (Go, Python, Shell, etc.) with a solid engineering-oriented mindset focused on automation and tooling development.
• Domain Knowledge:
  Systematic and practical understanding of CI/CD methodologies, Infrastructure as Code (IaC), Observability paradigms, and Site Reliability Engineering (SRE) principles.
• Soft Skills:
  
  Exceptional problem-solving abilities, sharp technical judgment, and excellent cross-team communication skills to effectively collaborate in a fast-paced, dynamic environment.

Preferred Qualifications (Plus):

• AI/ML Infrastructure
  
  Experience:
  
  Familiarity with MLOps practices, model serving/inferencing frameworks (e.g., vLLM, TGI, Triton Inference Server), and experience managing GPU clusters for AI/ML workloads.
• Large-Scale Systems:
  Proven track record working with…