Sr Mgr, Forward Deployed Engineer, Research Systems

Job description

Role & responsibilities People Leadership & Organisational Capability • Lead, coach, and develop a multi-disciplinary team that may include software engineers, application developers, business systems analysts, technical product owners, integration specialists, and platform leads. • Set clear objectives, establish accountability, conduct meaningful performance and career-development conversations, and build succession and capability plans. • Own workforce planning, role design, hiring, onboarding, retention, and the effective use of employees, contractors, and strategic partners. • Create an inclusive, high-performing culture focused on scientific impact, engineering excellence, customer partnership, innovation, and continuous learning. • Develop future leaders and delegate platform, product, and delivery accountabilities to appropriate team members while maintaining effective oversight. • Define team operating mechanisms, capacity plans, communities of practice, and technical standards that enable consistent delivery across multiple products and squads. Research Technology Strategy & Stakeholder Partnership • Partner with research scientists and R&D leaders to understand scientific workflows, identify high-value technology opportunities, and shape an integrated Research IT strategy and roadmap. • Own a portfolio of research systems and capabilities, aligning priorities, investments, resources, dependencies, risks, and outcomes with business and scientific objectives. • Represent Research IT in governance forums and communicate strategy, progress, decisions, risks, and value to senior stakeholders. • Build trusted partnerships across Product Management, Enterprise Architecture, Data and AI, Cybersecurity, Quality, Privacy, Infrastructure, and global R&D functions. • Champion user-centred discovery, product adoption, change management, and measurable value realization across scientific communities. • Supervise external trends in research informatics, laboratory automation, scientific computing, cloud, data, and AI and translate them into pragmatic opportunities. Research Platforms, Architecture & Integration • Provide strategic and technical oversight for research platforms such as ELN, LIMS, SDMS, laboratory instrument integrations, workflow solutions, scientific data platforms, and automation capabilities. • Define target-state architecture, product roadmaps, integration patterns, reusable services, data flows, and modernization plans in partnership with enterprise and solution architects. • Ensure solutions are interoperable, scalable, reliable, supportable, secure, and aligned with enterprise architecture and cloud standards. • Guide technical design decisions across APIs, microservices, event-driven architecture, workflow orchestration, data models, identity, observability, and platform engineering. • Drive rationalization of fragmented applications and technical debt while protecting business continuity and scientific productivity. • Enable responsible adoption of AI-assisted research and engineering capabilities, with appropriate governance for regulated and validated environments. Product Delivery & Operational Excellence • Lead delivery across multiple products and workstreams using Agile and product operating model principles, from discovery and business case through implementation, adoption, operations, and retirement. • Establish portfolio governance, delivery cadences, outcome metrics, release plans, dependency management, financial controls, and transparent risk escalation. • Ensure engineering excellence across secure SDLC, CI/CD, automated testing, validation, documentation, observability, incident management, service management, and production readiness. • Own service reliability and lifecycle health for assigned platforms, including upgrades, capacity, resilience, disaster recovery, vendor roadmaps, technical debt, and end-of-life planning. • Manage strategic suppliers and delivery partners through clear outcomes, statements of work, service levels, quality measures, performance evaluations, and commercial discipline. • Use operational, adoption, delivery, quality, and financial metrics to drive prioritization and continuous improvement. Quality, Risk & Compliance • Ensure research systems align with applicable security, privacy, data integrity, records management, intellectual property, quality, and regulatory requirements. • Partner with Quality and business system owners to apply risk-based computer system validation, change control, periodic review, audit-trail review, and inspection-readiness practices where required. • Maintain clear system ownership, decision rights, controls, documentation, and traceability throughout the technology lifecycle. • Lead or support major incident, deviation, audit, and corrective-and-preventive-action activities, ensuring root causes and systemic improvements are addressed. • Promote responsible AI, data stewardship, and secure-by-design behaviours across the team and partner ecosystem. Qualifications Required • Bachelors degree in Computer Science, Information Technology, Engineering, Bioinformatics, Life Sciences, or a related discipline; an advanced degree is advantageous. • 15+ years of progressive experience in technology product management, software engineering, research informatics, laboratory systems, or enterprise application delivery. • 7+ years of formal people-leadership experience, including direct management of managers, technical leads, or multiple individual contributors in a matrixed or global environment. • Demonstrated success building, developing, and retaining high-performing technical teams and leading workforce planning, hiring, performance management, and career development. • Proven ownership of a portfolio of complex technology products or platforms from strategy and investment planning through delivery, operations, modernization, and retirement. •