Sr Mgr, Forward Deployed Engineer, Research Systems

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.
• Experience partnering with scientific or R&D stakeholders and translating complex research needs into practical technology strategies, roadmaps, and solutions.
• Solid understanding of enterprise architecture, cloud platforms, application integration, APIs, data management, DevSecOps, observability, and modern engineering practices.
• Experience with laboratory or research systems and integrations, such as ELN, LIMS, SDMS, instrument software, workflow platforms, or scientific data environments.
• Understanding of regulated or validated systems, risk-based computer system validation, data integrity, change control, secure SDLC, and applicable GxP principles.
• Demonstrated ability to manage multiple initiatives, budgets, capacity, vendors, dependencies, risk, quality, and executive-level communications.
• Strong critical thinking, business insight, decision-making, negotiation, and influencing skills, with the ability to operate effectively across technical and non-technical audiences.
• Excellent written and verbal communication skills and a record of building trusted partnerships across global, cross-functional organizations.

Preferred

• Experience supporting pharmaceutical discovery, medicinal chemistry, synthetic development, biologics, or other research-intensive life sciences environments.
• Experience leading managers or senior technical leads and scaling a multi-layered organisation across locations.
• Knowledge of Design-Make-Test-Analyze workflows, laboratory automation, scientific computing, cheminformatics, bioinformatics, high-performance computing, or AI/ML-enabled research.
• Experience modernizing legacy research platforms and integrating laboratory systems with cloud, data, workflow, and analytics services.
• Relevant certifications in cloud, product management, Agile, architecture, service management, or project/program management.