Software Engineer III - Platform Tooling Development

As an Software Engineer III in the Collaboration and Communication Product Line, you will design and implement cloud contact center infrastructure and application components using Amazon Web Services (AWS) and Amazon Connect. You will build scalable, resilient platforms and integrations using Python and Terraform. You will partner with product, application, and infrastructure teams to define priorities, deliver iteratively, and improve reliability, performance, and cost efficiency. You will apply strong engineering practices across design, build, testing, deployment, and operations.

Join a Collaboration and Communication engineering team at a leading global financial institution focused on modern, secure employee communications. You will help build cloud contact center capabilities that enable client-facing teams to serve customers efficiently and reliably. This role offers hands-on ownership across infrastructure, application components, and integrations in a large-scale environment. You will work with experienced engineers in a collaborative culture that values inclusion, continuous learning, and practical innovation.

You will contribute to modern engineering practices including infrastructure as code, automation, and observability. You will also help the team adopt approved AI-assisted engineering approaches responsibly by setting clear validation expectations for quality, security, and correctness.

Job responsibilities

• Design cloud contact center infrastructure and application components that scale reliably in public cloud ecosystem – AWS. Build secure and efficient distributed systems/components such as microservices based architecture or message queueing platforms.
• Implement infrastructure as code using Terraform to provision, deploy and manage cloud resources leveraging AWS Cloud. Develop and maintain backend and/or frontend services and integrations to support contact center workflows. Build and improve CI/CD pipelines to enable secure, repeatable deployments.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Migrating and deploying applications to container orchestration platforms such as AWS ECS, EKS, Fargate, Kubernetes, Docket etc. clusters via CICD pipelines and automations. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Automating software development lifecycle, facilitating rapid and reliable application delivery.