Senior Vice President leading global engineering delivery for Confluence's investment data solutions. Overseeing multiple product lines and ensuring effectiveness across engineering teams.
Responsibilities
Architect and implement a unified global delivery model across local, near-shore, and offshore sites.
Establish and mature global delivery centres (CoEs) to centralise capabilities and drive scalability.
Optimise engineering organisation design, role clarity, and leadership layers for efficiency and predictability.
Define and implement common delivery frameworks, SDLC standards, and performance metrics across all teams.
Lead adoption of Artificial Intelligence across the development lifecycle, including:
• Embedding AI-assisted tools for coding, testing, and documentation.
• Introducing AI-driven analytics for delivery forecasting, quality prediction, and resource optimisation.
• Championing continuous learning and governance around emerging AI technologies in software engineering.
Build strong cross-functional alignment with Product, Operations, and Customer Success to ensure delivery reliability and speed.
Develop and mentor the engineering leadership team; strengthen management capability and accountability.
Drive continuous improvement in planning, release cadence, and quality across product lines.
Lead global workforce planning, talent strategy, and vendor integration to achieve optimal cost, agility, and skill mix.
Own engineering budgets, capacity planning, and delivery performance reporting.
Requirements
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related technical discipline.
15+ years in software engineering leadership, including leading large (200+) globally distributed organisations.
Proven success designing, building, and scaling global delivery centres or CoEs (local/near-shore/offshore).
Deep experience harmonising diverse teams and cultures into cohesive global operating models.
Expertise in SDLC optimisation, delivery governance, and process standardisation across multiple product domains.
Demonstrated record of improving throughput, quality, and predictability at scale.
Strong people leadership background: building high-performing management layers and leadership pipelines.
Advanced knowledge of cloud computing, software architecture, and SaaS scalability frameworks.
Operational discipline in metrics, planning, and continuous improvement frameworks.
Master’s degree in Technology Management, Engineering Management, or Business Administration (MBA) (Desirable).
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