Senior DevOps Engineer (Azure + Databricks, MLOps)

AppRecode is looking for a Senior DevOps / MLOps Engineer to join a client building a cloud-based AI/ML platform on Azure + Databricks.

The role is fully focused on MLOps infrastructure and automation – you will not develop or train models. Your mission is to ensure that existing ML models run reliably, securely, and at scale in production.

Project overview

The client is building an enterprise-grade AI/ML platform on Azure Databricks with a strong focus on:

• Infrastructure automation (Terraform + CI/CD)
• Reliable and observable ML pipelines
• Integration with core Azure services (Key Vault, Storage, ADF, Synapse)
• Access, data, and model governance via Unity Catalog and MLflow

You will join a long-term initiative working closely with Data Engineers and Data Scientists, where DevOps/MLOps is a key success factor.

Responsibilities

• Design and automate Databricks infrastructure using Terraform and CI/CD pipelines (Azure DevOps or GitHub Actions).
• Deploy and maintain environments for:
  • model training,
  • model versioning,
  • monitoring, and
  • reliable production execution in Databricks.
• Integrate Databricks with Azure components:
  • Azure Key Vault
  • Azure Storage
  • Azure Data Factory (ADF)
  • Azure Synapse
• Manage access, data lineage, and governance within Unity Catalog and MLflow.
• Collaborate with Data Scientists and Data Engineers to operationalize models and build stable production workflows.
• Apply DevOps best practices for:
  • security,
  • scalability,
  • infrastructure-as-code and lifecycle management.
• Continuously improve deployment automation, monitoring, and operational processes for the ML platform.

Required experience

• Proven hands-on experience with Databricks:
  • workspaces, clusters, jobs, Delta Lake.
• Strong knowledge of Azure Cloud services and how they integrate with Databricks.
• Solid experience with:
  • Terraform
  • CI/CD automation (Azure DevOps or GitHub Actions).
• Scripting skills in Python and/or Bash.
• Experience working in distributed / remote teams.
• Fluent English – comfortable with daily communication with the client and team.

Nice to have

• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) – for context only (not for day-to-day work).
• Experience with Docker or Kubernetes.
• Background as a Data Engineer or DevOps Engineer working on ML/AI use cases, especially on Azure Databricks.

Candidate profile

• You come from a Data Engineering or DevOps background.
• You have real-world experience building and maintaining Azure Databricks environments for ML/AI workloads.
• You are comfortable in a role that focuses entirely on:
  • infrastructure,
  • automation,
  • reliability of ML models in production,
    rather than data science or model training.

Role: Senior DevOps Engineer (MLOps / Azure Databricks)
Start: ASAP
Type: Long-term project
Language: English (working language)

What AppRecode offers

• 20 days of paid annual leave plus public holidays.
• 5 paid sick days per year.
• Remote-first work environment.
• Friendly and supportive team culture.
• Personal development plans and access to experienced mentors and technical leaders.
• Reimbursement for sports activities and professional certifications (after probation).
• Ongoing learning opportunities: internal trainings and knowledge-sharing sessions.
• Free English classes if you want to further improve your communication skills.