Cloud DevOps Engineer

About the job

SpaceSense is now part of xFarm, as their Geospatial entity. xFarm Technologies is a European tech company focused on the digitalisation of the agri-food sector, providing innovative tools that can support farmers and stakeholders in the management of their businesses.

The company offers digital solutions such as apps for farm management, connected sensors, support in digital transformation projects, algorithms applied to agriculture and training activities for the whole sector.

xFarm Technologies supports the work of 450,000+ farms belonging to more than 100 supply chains on 7 million hectares in more than 100 countries worldwide.

Join us at xFarm Technologies and be a part of the digital transformation in agriculture, contributing to a sustainable future!

The GeospatialAI team, in charge of building AI models on top of satellite imagery inside xFarm products, is looking for a Cloud DevOps Engineer. You will be responsible for designing, implementing, and maintaining a robust cloud infrastructure to support scalable geospatial data ingestion, processing, and analytics workflows. You will work closely with developers, data engineers, and machine learning teams to ensure smooth deployments, high availability, and cost-effective use of cloud resources.

Key Responsibilities

• Infrastructure design and implementation:
  Develop and manage infrastructure-as-code (IaC) solutions to build scalable, secure, and reliable cloud infrastructure on GCP to support geospatial data pipelines, APIs, and web applications.
• CI/CD Implementation:
  Build and manage CI/CD pipelines to automate deployment and delivery processes for microservices and machine learning models.
• Containerization & Orchestration:
  Develop, deploy, and manage containerized applications using Docker and Kubernetes.
• Monitoring & Logging:
  Set up and manage tools like Cloud logging, Prometheus, Grafana or Datadog to monitor system performance, track errors, and optimize resource usage.
• Data Pipeline Optimization:
  Collaborate with data engineers to optimize distributed computing workflows for processing large-scale geospatial data (e.g., Apache Beam, Dataflow).
• Security & Compliance:
  Implement robust security practices, including IAM, VPCs, firewalls, and monitoring, ensuring compliance with industry standards.
• Cost Management:
  Analyze and optimize cloud costs, balancing performance and budget.

Minimum Qualifications

• 3-5+ years of experience in cloud infrastructure and DevOps, with a strong focus on Google Cloud Platform (GCP)
• Experience with infrastructure-as-code (IaC) tools such as Terraform or Pulumi
• Proficiency with containerization tools (Docker) and orchestration systems (Kubernetes, preferably GKE).
• Experience with building and optimizing CI/CD pipelines using GitLab CI/CD or ArgoCD
• Hands-on experience with monitoring tools (Google Cloud Monitoring, Prometheus, Grafana) and logging solutions.
• Experience with SRE practices like incident response, error budgeting and post-mortem analysis to reduce downtime
• Experience with setting up fault-tolerant architectures, disaster recovery, backups, and automated failovers
• Knowledge of GCP Cost Management and techniques for tracking and reducing cloud costs
• Solid understanding of networking in cloud environments (VPC, load balancing, DNS, firewalls).
• Proficiency in English (written and oral) to communicate effectively in an international team.

Preferred Qualifications

• Knowledge of cloud-native design patterns and best practices for scalability and fault tolerance.
• Experience with large-scale geospatial data pipelines with frameworks like Apache Spark, Apache Beam, or Dask
• Understanding of GCP security services (IAM, Cloud Identity, Cloud Secret Manager) and implementing best security practices
• Python scripting skills for DevOps automation or workflow orchestration.
• Exposure to MLOps practices and tools like Vertex AI, Dataflow, and BigQuery ML
• Working knowledge of AWS cloud services is a plus

Educational Qualifications

• Degree:
  A Master's degree in Computer Science, Software Engineering, or a closely related field.
• Certifications:
  Google Cloud certifications such as Google Cloud Professional DevOps Engineer or Cloud Architect are highly valued

Soft Skills

• Collaborative Team Player:
  Work effectively with developers, data scientists, and product teams.
• Problem-Solver:
  Strong skills in diagnosing and resolving infrastructure/application issues in production environments
• Detail-Oriented:
  Strong focus on system reliability, security, and optimization.
• Proactive:
  Eager to identify improvements and take ownership of the cloud infrastructure.
• Documentation & Training:
  Ability to create documentation for cloud infrastructure, DevOps processes, and train team members

What We Offer

• Cutting-edge tech:
  Work with modern cloud-native stacks, geospatial data at scale, and advanced ML pipelines.
• Work in an international context:
  Collaborate with colleagues and partners from around the globe.
• Be part of a fast-growing company:
  Join a team that's rapidly scaling its impact in the ag-tech industry.
• Work in ag tech:
  Contribute to innovative solutions that are transforming agriculture using cutting-edge technology.
• Flexible environment:
  Enjoy a collaborative and innovative workplace where creativity and continuous improvement are valued.