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Senior AI Data Engineer

Scribd, Inc.
Vancouver, CAN
Full Time
Senior
Hybrid
5 days ago
PythonSQLDatabricksUnity CatalogApache AirflowSpark
Free

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About The Team

  • The Data Platform team sits within Scribd's Infrastructure organization and is responsible for the data infrastructure, governance, and enablement that powers the entire company.
  • We own the foundational layers that make trusted data accessible — from our Medallion Architecture and Unity Catalog in Databricks, to the semantic and AI layers that sit on top.
  • This is a high impact team at the center of Scribd's AI adoption push.

About The Role

  • We're looking for a Senior AI Data Engineer to lead the AI engineering workstreams on the Data Platform team.
  • This role has three dimensions: building data infrastructure for AI use cases, supporting stakeholders in shipping data products faster with AI, and helping our own team accelerate development through AI tooling.

What You'll Do

  • Own the deployment path for Databricks Apps — creating the infrastructure and guardrails that let non technical users bring their AI applications to production safely and consistently.
  • Build the AI layer on top of Scribd's Medallion Architecture and Semantic Layer — connecting AI agents and agentic workflows to governed data, and enabling non technical users to get self service answers.
  • Build AI skills and agents on top of our existing declarative tooling — giving platform stakeholders the interfaces they need to ship pipelines faster.
  • Partner with teams across the organization to identify the right AI tools, frameworks, and agentic patterns that accelerate data product development and broader AI adoption.
  • Identify and embed AI tools into how the Data Platform team writes, tests, and ships code — making AI assisted development a standard part of our engineering workflow.
  • Establish guardrails to ensure AI generated code, queries, and pipelines are correct, consistent, and production ready.
  • Help define and evolve data modeling and metadata patterns required to support AI use cases (e.g., context, documentation, discoverability).
  • Mentor other engineers and help define what great AI data engineering looks like at Scribd.

You Have

  • 5+ years of data engineering experience, with at least 1 year focused on AI/ML infrastructure or LLM powered applications.
  • Strong proficiency in Python and SQL; comfort working across the full data stack from ingestion to serving.
  • Hands on experience with Databricks and cloud data platforms (Unity Catalog experience a strong plus).
  • Experience building or integrating NLP/LLM based systems — RAG pipelines, semantic search, agent frameworks, or natural language interfaces.
  • Working knowledge of how modern LLMs are trained, aligned and evaluated (RLHF, fine tuning, prompt engineering, retrieval patterns) and the judgment to know when each approach is the right tool.
  • A solid understanding of data governance, access control, and what it means to build on top of trusted data.
  • A security first mindset when building AI surfaces, including secret management, encryption at rest and in transit, and responsible handling of sensitive and PII data across AI pipelines and workflows.
  • The ability to work autonomously on ambiguous problems and drive them to production.
  • Strong communication skills — you can explain complex systems to technical and non technical audiences alike.

Nice to Have

  • Familiarity with metrics as code frameworks or semantic layer tooling (e.g., Statsig, dbt Semantic Layer).
  • Prior experience in a platform or infrastructure team serving internal stakeholders.
  • Experience evaluating AI model outputs, including building eval harnesses, defining quality metrics, and catching regressions before they reach production.
  • Working knowledge of terraform, or strong systems thinking to reason confidently about infrastructure changes without necessarily owning the code.

Compensation

  • In Canada, the reasonably expected salary range is between CAD 162,000 and CAD 205,000.
  • This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.

Benefits At Scribd, Inc.

  • Scribd Flex (flexible work model).
  • Comprehensive health, dental, and vision coverage.
  • Mental health support and disability coverage.
  • Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals.
  • Paid parental leave and family support benefits.
  • Retirement matching and employee equity.
  • Learning and development programs and professional growth opportunities.
  • Wellness and home office stipends.
  • Complimentary access to the Scribd, Inc. suite of products.
  • Enterprise access to leading AI tools.

Workplace Arrangement

  • Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture.
  • Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location.

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