Director Software Engineering

Sci Val is Elsevier’s research-analytics platform. It helps universities, research institutions and funding organizations evaluate research performance, benchmark against peers, understand collaboration networks, identify emerging research areas, and support evidence-based strategic decisions. Sci Val is built on trusted, connected research data, including Scopus. Learn more about Sci Val.

As an Engineering Director supporting Sci Val, you will lead multiple engineering teams responsible for delivering a scalable, secure, and data-intensive analytics platform. You will partner closely with Product, Data, Architecture, Quality Engineering, Security, UX and commercial stakeholders to shape technical strategy, modernise platform capabilities, and enable AI-assisted and agent-ready experiences for customers. You will play a key leadership role in driving engineering excellence, developing technical talent, and ensuring the successful delivery of technology roadmaps that support research analytics and discovery solutions.

• Lead Sci Val’s engineering strategy and technical direction in partnership with Product, Data and Architecture.
• Define and uphold architectural standards across search, data, analytics, APIs and platform integration, aligned with Elsevier governance.
• Balance engineering excellence, innovation, cost efficiency and pragmatic delivery across the platform.
• Lead distributed engineering teams across frontend, backend, data and quality engineering.
• Hire, coach and develop high-performing 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 strong engineering standards for code quality, testing, release management, observability, security and operational resilience.
• Establish clear operating models for technical debt, production incidents, operational risk and partner delivery.
• Lead platform modernisation, consolidation and adoption of shared technology foundations to improve scalability, reliability and cloud-cost efficiency.
• Partner with Product, UX, Data and customers to improve Research Analytics workflows and enable AI-assisted, agent-ready experiences.
• Communicate technical trade-offs, dependencies, risks and delivery progress clearly to senior stakeholders and roadmap forums.

• Experience in software engineering, including significant experience leading engineering managers, engineering leads and distributed teams across multiple geographies and time zones.
• Proven experience delivering large-scale, data-intensive software products in production.
• Demonstrated success setting technical strategy and delivering technology roadmaps.
• Demonstrated 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, particularly within research and scholarly domains.
• Familiarity with analytics-driven systems, knowledge graphs or metadata-rich datasets.
• Experience delivering AI-enabled product capabilities such as summarization, guided workflows, intelligent search or decision support.
• Understanding of making data platforms accessible to AI agents through APIs, metadata, data contracts or MCP-compatible interfaces.
• Experience with AI adoption in SDLC streams.

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our…