• Own and drive technical roadmap across platform engineering, ensuring work is sequenced and aligned to leadership priorities • Make the platform AI-native, investing heavily in modern AI-powered dev workflows • Own cloud infrastructure at production scale. Write and maintain Terraform across our AWS footprint. Own the CI/CD template layer inherited by all service teams. • Own IAM at scale - Maintain and extend roles, policies, and permission boundaries across hundreds of services. Automate enforcement, not just review. • Eliminate toil through automation and self-service - Build the modules and tooling that allow teams to stand up services, manage deployments, and resolve issues without routing through a platform engineer. • Set and uphold expectations for delivery, reliability, and team accountability • Maintain platform health and delivery outcomes, including ownership of incident response and on-call management • Ensure platform systems are reliable, scalable, and meeting business needs

• Build and run internal platform infrastructure • Build, operate and maintain resilient, scalable platform foundations across environments, working from agreed designs and standards. • Support and run services on Azure and AWS, applying least‑privilege access, audited controls and automation as standard. • Implement deployment workflows, self‑service capabilities, golden paths and reusable templates that help teams ship safely and efficiently. • Implement and maintain infrastructure using Terraform, with modular, DRY patterns, appropriate testing and CI/CD integration. • Apply SRE principles in day‑to‑day work, supporting capacity planning, reliability improvements and secure‑by‑default patterns. • Implement logging, metrics and tracing. Create dashboards and alerts. • Participate in on‑call rotations and contribute to root cause analysis and continuous improvement. • Work closely with development, security and operations teams to deliver platform capabilities, execute agreed priorities and manage operational risk effectively.

• Contribute to the design, development, and operation of core components of Abnormal’s data platform. • Build tools and services that make it easy for other teams to adopt and scale data systems. • Help automate infrastructure and operations to improve reliability, performance, and scalability. • Apply cutting-edge GenAI techniques to build smarter developer and operator experiences. • Collaborate across engineering teams to solve scalability and reliability challenges. • Take ownership of projects, delivering features end-to-end with guidance from senior engineers.

• Identify and drive where ML/AI creates the most value across Productivity's user journeys • Toolify existing Productivity functionality so LLMs and agents can act on it • Partner with product, design and other engineering teams to shape AI strategy for Productivity • Set technical patterns and standards for how ML/AI gets applied and shipped across the team • Unblock organisational-level technical challenges that a single team can't solve alone • Mentor engineers and help raise the craft of applied ML engineering across the group • Balance speed and rigour, shipping AI features that hold up at Canva's scale • Translate shifts in user needs and the product roadmap into ML/AI priorities