• Design, build, ship, and maintain core capabilities for North’s Agents & Automations platform. • Build product and platform features that help users create, run, debug, evaluate, and improve agents and automations. • Own features end-to-end, from technical design through implementation, testing, launch, and iteration. • Work across the stack, from frontend product surfaces to backend systems, depending on what the product needs. • Make practical technical decisions that balance speed, quality, depth, and user impact. • Collaborate closely with product, design, modelling, customer-facing teams, and other engineers to define the right outcomes and ship measurable improvements. • Use AI actively in your work, while staying intellectually engaged and accountable for the quality and reliability of what you ship.

• Setting and driving front-end technical strategy across the Account Experience teams, from architecture and component-system decisions through to hands-on implementation where it counts • Owning the architecture of a complex, data-dense merchant platform — the patterns, state management, and performance characteristics that hold up as the surface area grows • Shaping how Primer AI Companion matures as a first-class merchant interface, including the front-end architecture that makes a conversational surface feel native to the platform • Holding the experience coherent across Account Setup, Monitors, Workflows, and Auditing — building the shared component and design-system foundations that stop the areas drifting apart • Leading engineers across teams without direct authority, through code, design reviews, and technical mentorship that raises the front-end bar around you • Owning the things that are easy to neglect: accessibility, performance budgets, and front-end observability as first-class concerns, not afterthoughts • Partnering with Product and Design, and with backend engineers across teams, to shape decisions where front-end constraints or opportunities are material

• Design and build REST APIs and web applications for cloud services and on-site device configuration, monitoring, and management • Develop intuitive management UIs for both cloud-based workflows and local hardware deployment • Architect backend services that bridge cloud (AWS) and on-premises AI compute environments • Design low-latency database schemas covering job tracking, results storage, audit logging, and device management • Build and maintain containerized AI inference pipelines deployed on both cloud and dedicated GPU hardware • Implement end-to-end observability (telemetry, logging, alerting) across distributed environments • Identify and resolve performance bottlenecks in inference pipelines and large binary data workflows • Ensure software meets regulatory compliance standards (FDA 21 CFR Part 11/820, SOC2) • Partner closely with ML Engineering and Research teams to bring models into production • Contribute to design reviews, architecture discussions, and incident response rotations • Produce technical documentation for API specs, deployment guides, and regulatory submissions

• Shape the technical roadmap and architecture for enterprise-grade Digital Menu Board solutions used by massive, global QSR brands. • Guide, mentor, and technically manage an agile team of talented engineers, fostering a culture of continuous improvement. • Architect and scale platforms using TypeScript, NestJS, Express, Angular/React/Svelte, and cloud-native infrastructure. • Lead internationalization initiatives and travel occasionally to collaborate with global stakeholders and clients. • Conduct code reviews, establish best practices, and unblock technical hurdles. • Define, document, and enforce technical standards, coding guidelines, and architectural patterns across the organization. • Own and execute the i18n strategy to ensure the platform seamlessly adapts to diverse regional, language, and localization requirements. • Partner closely with DevOps, Product Management, and executive stakeholders to align technical roadmaps with business objectives. • Support cloud infrastructure deployments and platform scalability initiatives in partnership with DevOps teams. • Identify and remediate architectural bottlenecks to improve system performance, security, and maintainability.