Top Tech Jobs & Startup Jobs in Belfast

Own product areas across AI investing and other financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Lead technical direction and hands-on execution for major products, systems, and engineering initiatives. Design scalable and reliable backend, frontend, API, database, and infrastructure solutions; write code; make architecture trade-offs; solve production issues; and improve testing, security, observability, and development practices. The role also leads critical initiatives, mentors engineers, and translates ambiguous product challenges into clear technical plans.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Own technical direction and execution for major products and systems. Design scalable, reliable architectures across backend, frontend, APIs, databases, and infrastructure; write production code; lead architecture decisions; solve complex production problems; improve engineering quality, testing, security, and observability; drive critical initiatives; and mentor engineers across teams.

Build and maintain production-grade iOS applications using Swift and SwiftUI, integrating AI through backend APIs. Design reliable AI interaction patterns, optimize performance and memory, support concurrency and background tasks, capture user feedback, and collaborate with backend and machine learning engineers. Maintain App Store quality, monitor production issues, and deliver responsive, stable, and efficient user experiences.

Own company-wide performance management, OKR planning, people processes, organizational analytics, dashboards, HR system requirements, and workflow improvements. Partner with leadership to strengthen accountability, execution, career development, promotions, performance reviews, and company culture. The role also supports strategic people initiatives, improves employee experience, and drives scalable organizational effectiveness in a fast-paced, high-growth environment.

Own the company-wide performance management and OKR framework, including planning, tracking, reviews, calibration, promotions, and career development. Analyze people and operational data, build organizational dashboards, define HR systems requirements, improve workflows, and lead initiatives that strengthen accountability, execution, culture, and employee experience. Partner with company leaders on scalable people processes and strategic organizational projects in a fast-paced environment.

Own the company-wide performance management and OKR frameworks, including planning, tracking, reviews, calibration, promotions, and career development. Analyze people and operational data, build organizational performance dashboards, define HR system requirements, improve workflows, and partner with leaders to strengthen accountability, execution, culture, and employee experience. Support strategic people initiatives and organizational projects in a fast-paced, high-growth environment.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, UX, and reliability. Define offline and online evaluation frameworks, incorporate human feedback, guide prioritization, and ensure AI features are understandable, predictable, safe, and trusted by users.

Own the end-to-end product strategy and execution for AI agent systems. Define technical and behavioral requirements, evaluate model performance, guide trade-offs across quality, latency, cost, reliability, and user experience, and partner closely with ML, backend, and mobile engineers. Establish evaluation frameworks, prioritize roadmaps, drive rapid and safe delivery, and ensure AI features are predictable, trustworthy, and valuable to users.