Senior AI Data Engineer
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Key skills for this role
About the Role
Scribd is seeking a Senior AI Data Engineer to lead AI engineering workstreams on the Data Platform team. You will build data infrastructure for AI use cases, support platform stakeholders, and accelerate development through AI tooling.
Key Skills for This Role
Responsibilities
- 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
- Build AI skills and agents on top of 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
- 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
- Mentor other engineers and help define what great AI data engineering looks like at Scribd
Requirements
- 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)
- 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
- 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
Full Job Posting
About Scribd, Inc.
- Scribd, Inc. is on a mission to advance human understanding through products like Scribd, Slideshare, Everand, and Fable.
- We support a culture where employees can be real and be bold, and we hire for GRIT: Goals, Results, Innovative ideas, and Team.
About The Team
- The Data Platform team is responsible for data infrastructure, governance, and enablement across the company.
- We own foundational layers from Medallion Architecture and Unity Catalog in Databricks to semantic and AI layers.
About The Role
- We're looking for a Senior AI Data Engineer to lead AI engineering workstreams on the Data Platform team.
- This role has three dimensions: building data infrastructure for AI, supporting platform stakeholders with AI, and accelerating development through AI tooling.
What You'll Do
- Own the deployment path for Databricks Apps.
- Build the AI layer on top of Scribd's Medallion Architecture and Semantic Layer.
- Build AI skills and agents on top of existing declarative tooling.
- Partner with teams to identify the right AI tools and agentic patterns.
- Embed AI tools into the Data Platform team's engineering workflow.
- Establish guardrails for AI generated code and pipelines.
- Help define data modeling and metadata patterns for AI.
- Mentor other engineers.
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.
- Hands on experience with Databricks and cloud data platforms.
- Experience building or integrating NLP/LLM based systems.
- Working knowledge of modern LLMs.
- Solid understanding of data governance and access control.
- Security first mindset.
- Ability to work autonomously on ambiguous problems.
- Strong communication skills.
Nice to Have
- Familiarity with metrics as code frameworks or semantic layer tooling.
- Prior experience in a platform or infrastructure team.
- Experience evaluating AI model outputs.
- Working knowledge of terraform.
Compensation
- In Canada, the reasonably expected salary range is between CAD 162,000 and CAD 205,000.
- This position is also eligible for competitive equity ownership and comprehensive benefits.
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
- Paid parental leave and family support benefits
- Retirement matching and employee equity
- Learning and development programs
- Wellness and home office stipends
- Complimentary access to Scribd products
- Enterprise access to leading AI tools
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