MoneySmart Group

• Own production reliability outcomes for services (availability, scalability, cost-efficiency, and security) from early design through implementation and operations • Architect, deploy, and secure AWS cloud infrastructure following best practices • Lead incident response, RCAs and run post-incident reviews • Build and maintain “everything as code” infrastructure using Terraform/CloudFormation • Operate, scale, and evolve the container platform (Kubernetes/EKS/ECS) • Design, implement, and continuously improve CI/CD pipelines to enable fast, safe, and repeatable releases • Integrate security tools, practices, and controls into CI/CD and DevOps workflows including container image scanning, runtime security controls, IAM best practices, and secure secret management • Continuously assess and reduce cloud security risks through automated guardrails, compliance enforcement, and monitoring • Establish and mature observability practices (metrics, logs, traces, dashboards, alerting) to improve system visibility and reduce incident resolution time • Drive automation to eliminate operational toil across infrastructure provisioning, deployments, monitoring, access management, and routine maintenance tasks • Promote an AI-first engineering culture by leveraging AI-assisted tooling to accelerate scripting, documentation, troubleshooting, and operational analysis • Design and prototype agentic solutions for automating repetitive DevOps workflows • Mentor peers, define platform standards, and raise the engineering bar to improve consistency, resilience, and knowledge sharing across teams.

• Build, improve, and maintain software systems, with a focus on performance, reliability, and long-term maintainability • Deliver on key initiatives end to end from ideation and requirement understanding through analysis, technical design, development, testing, and product delivery • Take full ownership of assigned work, including implementation details, quality, edge cases, and follow-through after release • Write clean, well-structured, and well-tested code, ensuring appropriate test coverage and adherence to engineering standards • Use AI-assisted development tools and workflows to improve development efficiency, debugging, and documentation, while validating all outputs through sound engineering judgment • Collaborate with product, design, and other teams to ensure solutions are aligned with customer needs and broader system context • Continuously learn and improve, staying curious about better ways to build software and contributing learnings back to the team

• Own problems end-to-end, from fuzzy brief to shipped experience, across comparison, financial advisory, and discovery surfaces • Do the research, make the call, synthesize user insights into clear problem statements and design decisions the team can act on • Deliver the craft, high-quality wireframes, prototypes, and final UI that are thoughtful, precise, and technically feasible • Push back when it matters, challenge assumptions, ask the uncomfortable questions, and advocate for the right solution • Float well across squads partner with dedicated PMs and engineers, and actively shape design culture and practice as you go • Use AI as a tool, not a buzzword. Bring it into your workflow to move faster, explore wider, and design smarter