About The Role

Title: Senior Data Platform Engineer (AI Products)

Location: Dublin, hybrid, 3 days per week in the Storyful office
Type: Hands-on individual contributor / player-coach
Job description

Senior Data Platform Engineer (AI Products)

Storyful is building the next generation of data and AI products on top of complex, high-volume, multi-source content. We are looking for a hands-on Senior Data Platform Engineer to build the technical foundations that make those products scalable, reliable, and ready for production.

This is a senior individual contributor role for someone who is strongest in data engineering but comfortable operating across AI infrastructure, retrieval systems, cloud architecture, and product delivery. You will design and build the ingestion, processing, storage, and serving layers that power future AI and data products across Storyful.

You will work closely with machine learning engineers, software engineers, product managers, and leadership to turn raw structured and unstructured data into trustworthy product capabilities.

What you will do

Design and build scalable batch and streaming pipelines for structured, semi-structured, and unstructured data
Own the ingestion and processing architecture for documents, text, metadata, and other content sources
Build robust data workflows for parsing, chunking, enrichment, indexing, and retrieval
Create the platform foundations for AI products, including orchestration, data quality, observability, lineage, and cost-aware processing
Design storage patterns across object stores, relational databases, search/vector systems, and where appropriate graph or knowledge-based systems
Partner with ML and product engineering to productionise AI features, agentic workflows, and retrieval-backed user experiences
Define data contracts, schema evolution practices, and quality controls across services and teams
Improve reliability, freshness, and traceability of pipelines that feed customer-facing products
Contribute hands-on code while helping set engineering standards and mentoring other engineers

What good looks like in this role

Raw inputs from multiple sources become clean, versioned, monitorable assets that product and ML teams can trust
New datasets and content types can be onboarded quickly without fragile one-off pipelines
AI product features are built on observable, debuggable foundations rather than opaque glue code
Document processing and retrieval quality improve because content is structured well before it reaches the model layer
The team has clear standards for pipeline reliability, schema management, testing, and deployment

What we’re looking for

Strong experience in data engineering or platform engineering in production environments
Excellent Python skills and solid SQL fundamentals
Experience building reliable ingestion and transformation pipelines at scale
Strong understanding of data modeling across structured and unstructured datasets
Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, Temporal, or equivalent
Strong cloud engineering experience in AWS, GCP, or Azure, with clear transferability across platforms
Experience with infrastructure as code and modern deployment practices
Experience with distributed systems, event-driven patterns, and data-intensive applications
Familiarity with search, vector, or retrieval systems used in AI-backed products
Ability to work cross-functionally and act as a technical leader without losing hands-on depth

Particularly valuable experience

Document processing pipelines for PDF, HTML, text, or media-rich content
Search indexing, retrieval, semantic chunking, or RAG pipeline design
Graph databases, knowledge graphs, or entity/relationship-heavy systems
Data quality, lineage, observability, and governance in regulated or high-trust environments
Experience supporting agentic products with strong guardrails and human-in-the-loop controls
Experience in media, intelligence, risk, trust, or other information-dense domains

Why this role matters

This role will help Storyful move from promising AI features to durable AI products. The person in this role will lay the foundation that allows ML, GenAI, and agentic capabilities to work reliably on top of real-world data at production scale.

Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic under applicable law.

Reasonable Accommodation

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