About the role

Director of AI Data Platform at Zartis, shaping data infrastructure for next-gen AI solutions. Leading development, governance, and operational excellence in AI data readiness processes.

Responsibilities

Lead the development of a core AI Data Readiness platform that transforms fragmented enterprise data into clean, governed, and discoverable assets ready for AI consumption.
Serve as the primary architect of the data-to-AI lifecycle, ensuring both structured and unstructured data assets are AI-ready from day one.
Oversee the end-to-end processing lifecycle—including ingestion, parsing, and enrichment—to guarantee the accuracy and governance of all published assets.
Define standards and tooling for ingesting data from client systems (batch and streaming).
Build reusable connectors and canonical schemas to eliminate redundant, project-specific custom work.
Implement Data Contracts with upstream systems and downstream consumers to guarantee data integrity.
Establish automated validation gates for completeness, consistency, anomaly detection, and drift monitoring.
Ensure “Governance by Default,” including PII detection/redaction, encryption, and audit trails for GDPR and AI Act compliance.
Define and maintain SLAs/SLOs for ingestion pipelines (freshness, uptime, failure rates).
Optimize cloud-native infrastructure costs and implement robust monitoring and incident playbooks.
Serve as the lead architect for enterprise customers, designing high-performance AI data readiness strategies aligned with business goals.
Scale a specialized team of data and platform engineers.
Provide documentation, standards, and self-service capabilities for cross-functional teams.

10+ years of experience in data-heavy engineering or platform environments
2+ years leading platform or data engineering teams
Proven track record of delivering reusable internal data capabilities rather than one-off pipelines
Strong software engineering foundation with a platform mindset
Advanced Database Expertise
Mandatory experience with Vector Databases such as Pinecone, Milvus, or Weaviate
Proven ability to structure enterprise data for LLMs, including chunking, enrichment, embedding, and relationship mapping
Deep expertise in SQL, ETL/ELT, and data modeling
Strong experience with parsing, OCR, metadata enrichment, and unstructured pipelines
Experience with cloud-native architectures (Containers, IaC)
Strong operational mindset across monitoring, alerting, and cost management
Strong proficiency in LLM concepts and AI-ready data design
Nice to Have: Knowledge graph design and hybrid retrieval systems
Experience advising enterprise customers on AI transformation
Background in highly regulated industries (finance, healthcare, energy)

100% Remote Work
WFH allowance: Monthly financial support for remote working
Career Growth: Established career development program with 360º feedback to support progression
Training: Weekly allocated time for learning, including online courses (Pluralsight, Educative.io), English classes, books, conferences, and events
Mentoring Program: Opportunities to mentor, be mentored, or both
Zartis Wellbeing Hub (Kara Connect): Access to mental health professionals, nutritionists, physiotherapists, fitness coaches, and wellbeing webinars
Multicultural working environment: Tech events, webinars, online team-building activities, and company celebrations