Senior AI Data Engineer (RAG Foundations)

Location: Barcelona, Spain; full-time weekly schedule; day shift; travel required 10% of the time.

Company

hirify.global advances scientific discovery, diagnostics, and applied market solutions through instruments, software, consumables, services, and domain expertise.

What you will do

• Build and maintain governed AI-ready data products and pipelines with lineage, metadata, access controls, documentation, and reuse in mind.
• Establish data quality standards, quality scoring, and model-readiness criteria, addressing issues before they affect AI solutions.
• Partner with data owners, stewards, business stakeholders, subject matter experts, and IT teams to define authoritative sources, trusted meanings, and domain data models.
• Design retrieval foundations for structured and unstructured grounding, vector search, graph-based approaches, and semantic enrichment.
• Apply AI-assisted metadata generation, entity resolution, and content classification to improve data quality, scalability, and discoverability.
• Design scalable ingestion, integration, and storage frameworks across cloud and on-premises environments, and build reusable assets for AI engineers, data scientists, and analytics teams.

Requirements

• Strong data engineering experience building AI-ready data products, rather than only warehouse tables and dashboards.
• Hands-on familiarity with Microsoft Fabric, Snowflake, vector databases, graph stores, data contracts, lineage, and certification requirements.
• Experience with RAG foundations, including chunking, embedding, hybrid retrieval, and understanding the impact of retrieval quality on agent and AI behavior and outcomes.
• Ability to work within a business domain and partner with data stewards and subject matter experts to understand the meaning behind data.
• Ability to build reusable assets intended for additional consumers and use cases.
• Excellent communication skills and the ability to influence technical and non-technical audiences and build partnerships with domain experts, stewards, business stakeholders, Legal, Quality, and Security.
• Curiosity about AI opportunities, limitations, and emerging approaches, together with a skeptical and responsible implementation mindset.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.
• Typically at least 8+ years of relevant experience for entry to this level.

Culture & Benefits

• Work in a cross-functional AI pod with AI engineers, domain experts, business stakeholders, data owners, and platform teams.
• Contribute data products, reusable patterns, tools, and documentation to the broader enterprise ecosystem.
• Work across cloud and on-premises environments with a focus on governance, quality, reuse, and long-term value.
• Full-time schedule with day-shift hours and no stated end date.
• Pay and benefits vary by country, work location, role level, skills, experience, and education or training.