SVP, Development and Enterprise Architecture

Architecture & Platform Strategy

• Define and evolve the enterprise architecture vision across application, data, and AI layers, aligned to business strategy.
• Lead the transition to a platform engineering model enabling self-service, reusable capabilities, and developer acceleration.
• Architect systems that are cloud-native, API-first, event-driven, and designed for continuous change and scale.
• Establish patterns for AI integration, including model orchestration, feature reuse, and real-time decisioning.

• Define and execute an AI-first engineering strategy that embeds AI agents, and automation across the SDLC (design, coding, testing, deployment, and operations).
• Drive adoption of generative AI and machine learning to improve developer productivity, code quality, and delivery velocity.
• Establish governance, security, and risk management practices for responsible AI usage across engineering.

• Lead global engineering teams to deliver high-quality products and enhancements with speed, predictability, and quality.
• Modernize development practices through AI-assisted engineering, CI/CD, trunk-based development, and infrastructure as code.
• Own and improve key engineering metrics (e.g., DORA metrics, developer experience, cycle time, defect rates).
• Partner with Product to align delivery with business priorities, driving measurable customer and business outcomes.

• Partner with Product leadership to embed AI/ML capabilities directly into core products and workflows.
• Enable scalable data platforms and pipelines that support real-time insights and intelligent experiences.
• Promote reuse of data, models, and AI services across the organization to maximize leverage and consistency.

• Champion a “built-in quality” mindset with automation, AI-driven testing, and shift-left practices.
• Partner with QA leadership to evolve testing into an AI-enabled, continuous quality engineering discipline.
• Partnering with Information Security lead secure-by-design practices and application security modernization, including proactive risk detection and remediation.

• Build, lead, and inspire a high-performing global organization of engineers and architects.
• Upskill teams on AI-native development, modern architecture, and platform engineering practices.
• Foster a culture of innovation, experimentation, accountability, and continuous learning.
• Align organizational structure and talent to evolving business and technology priorities.

• Act as a thought leader on emerging technologies, particularly AI/ML, and their application to wealth management.
• Continuously assess industry trends to inform platform evolution and competitive differentiation.
• Influence executive stakeholders by translating technology strategy into business value and outcomes.
• Continually drive modernization of the existing technology base across cloud, data, AI, and distributed systems.

• Help establish lean governance, standards, and architectural guardrails to ensure consistency without slowing innovation.
• Help oversee budgets, resource allocation, and global delivery models to optimize efficiency and effectiveness.
• Ensure compliance with enterprise architecture standards, regulatory requirements, and security best practices.

• Continuously seeking insight into customer needs, industry trends, and emerging technologies.
• Ensuring engineering teams understand how the company’s technology creates a competitive advantage.
• Partnering with Product and Strategy leaders to ensure engineering investments support winning in current and future markets.
• Fin Tech experience is a plus, but not required

• Bachelor’s degree in computer science or related field (advanced degree preferred).
• 15+ years of experience leading large-scale engineering and architecture organizations.
• Proven track record of delivering complex, scalable, enterprise-grade platforms in a regulated environment (financial services preferred).
• Deep…