• Participate in example meetings • Lead example initiatives • Recruit new team members to example team • Mentor and develop existing team members

• Lead and influence cloud architecture decisions for new platforms and modernization initiatives, with a focus on AWS and hybrid cloud patterns. • Design and deliver cloud‑native and hybrid solutions that support the migration of legacy on‑prem .NET systems to modern, containerized, serverless, or Linux‑based runtimes. • Own Infrastructure as Code (IaC) implementations and automation strategies to ensure repeatable, secure, and scalable environments. • Build and operate production‑grade cloud services, emphasizing reliability, performance, security, and cost efficiency. • Partner with application teams to modernize CI/CD pipelines, deployment strategies, and runtime architectures. • Drive serverless‑first and platform engineering best practices, mentoring engineers and raising the overall cloud maturity of the organization. • Define and document reference architectures, operational patterns, and platform standards. • Support operational excellence, including incident response, root cause analysis, and participation in a rotating on‑call schedule. • Champion change, incident, and problem management practices within a DevOps/SRE‑aligned operating model. • Collaborate across infrastructure, networking, security, and vendor teams to ensure compliant, well‑designed application architectures. • Design and support business continuity and disaster recovery strategies aligned to enterprise availability and resilience goals. • Proactively address security and compliance concerns, ensuring platforms are hardened against evolving cybersecurity threats.

• Implement and deploy AI agents into internal Gatekeeper workflows. • Work directly with internal teams (Product, Marketing, Finance, Sales, Account Management, Operations, Professional Services) to understand processes and identify high-impact AI use cases. • Configure agent behaviour through prompts across different tools, rules and guardrails. • Integrate AI agents with existing systems, data sources and internal tools via APIs, webhooks and integrations. • Use Python for orchestration, data handling, light automation and evaluation. • Test, iterate and refine AI agents based on real usage and feedback. • Monitor deployed agents for accuracy, reliability and business impact, escalating issues where deeper platform changes are needed. • Collaborate with the Senior AI Platform Engineer on agent standards, tooling, observability, governance and ROI. • Document implementations and help establish repeatable internal AI deployment patterns.

• Design, implement, and manage platform architectures with a strong focus on CMC tenancy and multi-tenant scalability • Lead the development and integration of APIs, ensuring performance, security, and maintainability • Own data architecture, including logical and physical data models across systems • Plan and execute data migration strategies, including data mapping, transformation, validation, and reconciliation • Collaborate with cross-functional teams to translate business requirements into technical solutions • Establish and enforce platform engineering best practices, standards, and documentation • Monitor, troubleshoot, and optimize platform performance and reliability • Provide technical leadership and mentorship to junior and mid-level engineers • Participate in architecture reviews and contribute to long-term platform roadmaps