Zartis2mo ago

Director Of AI Data Platform

European UnionTechnical Directorexecutive

Data ScienceOtherData EngineeringDirector

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Quick Summary

Key Responsibilities

Unstructured Data & Indexing Layer (Core Ownership) - Lead the development of pipelines for unstructured data sources, including document parsing, OCR,

Technical Tools

Data ScienceOtherData EngineeringDirector

The Company and Our Mission

Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting-edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact.

Our teams bring deep expertise in AI-driven platforms, secure API architectures, and cloud-native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies — from strategy and discovery through to full product delivery — helping turn complex challenges into measurable outcomes.

With engineering hubs across EMEA and LATAM, and long-term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology — you will drive business impact and grow your career alongside industry leaders.

We are looking for a Director of AI Data Platform to help shape the foundational data infrastructure powering next-generation AI solutions.

The Project:

You will 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.

This is a strategic, high-impact role where you will serve as the primary architect of the data-to-AI lifecycle, ensuring both structured and unstructured data assets are AI-ready from day one. You will oversee the end-to-end processing lifecycle—including ingestion, parsing, and enrichment—to guarantee the accuracy and governance of all published assets.

What You Will Do:

Unstructured Data & Indexing Layer (Core Ownership)

- Lead the development of pipelines for unstructured data sources, including document parsing, OCR, and text normalization

- Own the indexing strategy beyond traditional SQL storage, architecting structures optimized for LLM consumption

- Design and oversee semantic chunking, embedding strategies, and hybrid search across Vector and Graph architectures

- Establish metadata extraction protocols to ensure high-fidelity knowledge capture for internal and client use

Data Ingestion & Standardization

- 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

Data Quality & Governance

- 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

Operational Excellence

- Define and maintain SLAs/SLOs for ingestion pipelines (freshness, uptime, failure rates)

- Optimize cloud-native infrastructure costs and implement robust monitoring and incident playbooks

Strategic Stakeholder Management (Dual Focus)

- Architect and manage the data infrastructure powering operational efficiency and internal IP

- Serve as the lead architect for enterprise customers, designing high-performance AI data readiness strategies aligned with business goals

Leadership & Delivery Enablement

- Lead and scale a specialized team of data and platform engineers

- Provide documentation, standards, and self-service capabilities for cross-functional teams

What You Will Bring:

- 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 mappingDeep 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)

What We Offer:

- 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