Engineering Director - AI-Driven Research Platform

RELX

Amsterdam

On-site

EUR 111,000 - 184,000

Full time

9 days ago

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Job summary

Elsevier's SciVal division seeks an Engineering Director to lead multiple engineering teams, guiding the technical strategy for a scalable, data‑intensive analytics platform used by researchers. You will partner with Product, Data, Architecture, Quality Engineering, Security, UX and commercial stakeholders to shape capabilities and enable AI‑assisted experiences.

You will drive engineering excellence, develop technical leaders and ensure delivery of technology roadmaps that support research

Qualifications

Experience leading engineering managers, leads and distributed teams across geographies and time zones.
Proven track record delivering large‑scale, data‑intensive software products in production.
Success setting technical strategy and delivering technology roadmaps.
Experience introducing AI‑assisted development practices across engineering teams.
Excellent communication, planning, influencing and stakeholder‑management skills.
Experience with large‑scale data ingestion, transformation, indexing and query optimisation.
Understanding of search, discovery and graph-based data relationships in research domains.
Familiarity with analytics‑driven systems, knowledge graphs or metadata-rich datasets.
Experience delivering AI‑enabled product capabilities such as summarization, guided workflows or intelligent search.
Understanding of making data platforms accessible to AI agents via APIs and data contracts.

Responsibilities

Lead SciVal’s engineering strategy and technical direction with Product, Data and Architecture.
Define and uphold architectural standards across search, data, analytics, APIs and platform integration.
Balance engineering excellence, innovation, cost efficiency and pragmatic delivery.
Lead distributed engineering teams across frontend, backend, data and quality engineering.
Hire, coach and develop engineers, engineering managers and technical leaders.
Own workforce planning, succession planning, performance management and resource allocation.
Drive planning, prioritisation and execution across multiple engineering teams and programmes.
Maintain high standards for code quality, testing, release management, observability and security.
Establish operating models for technical debt, production incidents and partner delivery.
Lead platform modernisation, consolidation and adoption of shared technology foundations.
Partner with Product, UX, Data and customers to improve Research Analytics workflows and AI‑assisted experiences.
Communicate technical trade-offs, dependencies, risks and delivery progress to senior stakeholders.