Director Software Engineering

In this role you will lead multiple engineering teams to deliver a scalable, secure data‑intensive analytics platform for SciVal. You’ll shape technical strategy with cross‑functional partners and drive platform modernization to enable AI‑assisted experiences for researchers and institutions. You will develop engineering talent, own technology roadmaps, and ensure delivery across complex programs. Join a mission to advance science by harnessing trusted research data at scale.

• flexible working hours
• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals
• country-specific benefits

• Define and lead SciVal's engineering strategy and technical direction with Product, Data and Architecture
• Set architectural standards across search, data, analytics, APIs and platform integration
• Balance excellence, innovation, cost efficiency and pragmatic delivery
• Lead distributed teams across frontend, backend, data and quality engineering
• Hire, coach and develop engineers and technical leaders; manage workforce planning and performance
• Drive planning, prioritisation and execution across multiple teams and programmes
• Maintain high engineering standards for code quality, testing, releases, observability, security and resilience
• Establish operating models for technical debt, incidents, risk and partner delivery
• Lead platform modernization for scalability, reliability and cloud-cost efficiency
• Collaborate with Product, UX, Data and customers to improve workflows and enable AI‑assisted experiences
• Communicate trade‑offs, dependencies, risks and progress to senior stakeholders

• Experience leading engineering managers and distributed teams across geographies
• Proven track record delivering large‑scale, data‑intensive software products
• Experience setting technical strategy and roadmaps
• Experience introducing AI‑assisted development practices
• Excellent communication, planning, influencing and stakeholder management
• Experience with large‑scale data ingestion, transformation, indexing and query optimization
• 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 (summarization, guided workflows, intelligent search)
• Understanding of making data platforms accessible to AI agents via APIs and data contracts
• Experience with AI adoption in SDLC streams

• communication
• planning
• influencing
• large-scale data ingestion/processing
• search and discovery technologies
• APIs and platform integration