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AI Product Specialist – Databricks Deployment

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Riverflex

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Location:
Netherlands , Rotterdam

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We are looking for an interim AI Product Specialist to support clients with the rapid deployment and scaling of AI products on Databricks. This is a hands-on, delivery-focused role for someone who can bridge data engineering, applied ML/analytics, and business value—and who is comfortable moving quickly from discovery to production. You will work with cross-functional teams to ensure AI products are deployable, governable, and measurable, while keeping stakeholders aligned on outcomes, risks, and ROI.

Job Responsibility:

  • Deploy and operationalize AI products on Databricks, working closely with data engineers, data scientists, and platform teams
  • Translate business goals into deployable product requirements, including data needs, success metrics, and rollout approach
  • Design and optimize pipelines and environments (lakehouse patterns, compute, orchestration) to support analytics and ML workflows
  • Drive the path from PoC to production, including implementation planning, technical decision-making, and delivery governance
  • Implement data governance and quality practices (data lineage, access, quality checks, compliance considerations) to meet enterprise standards
  • Act as a Databricks SME: advise on architecture choices, integration patterns, performance considerations, and operational readiness
  • Support value realization: define KPI/ROI frameworks with stakeholders and help communicate impact and adoption progress

Requirements:

  • 3–7 years in data product delivery, analytics engineering, applied AI, or similar roles (consulting experience is a plus)
  • Proven experience with Databricks in real delivery contexts (platform capabilities, deployment patterns, production considerations)
  • Strong understanding of data lifecycle and architecture (pipelines, lakehouse concepts, quality, governance)
  • Strong stakeholder management: able to align technical and business teams and keep delivery outcome-focused
  • Comfortable working in fast-moving environments, creating clarity and structure where it’s missing
  • Excellent communication skills—able to explain trade-offs, risks, and value in plain language

Nice to have:

  • Experience with ML lifecycle/ML Ops concepts (model deployment, monitoring, retraining triggers, feature management)
  • Familiarity with cloud platforms (Azure/AWS/GCP) and enterprise security/compliance constraints
  • Experience setting up or improving operating models for data/AI product delivery (ways of working, handovers, run/support)

Additional Information:

Job Posted:
February 03, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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