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. 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 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 Create and maintain APIs and integration patterns (for example, REST APIs) to connect systems and services. Implement authentication and authorization for applications using OAuth2 and JWT based authentications to safeguard data and services. Working with Real time data/media streaming such as kinesis, Kafka etc. Partner with engineering and stakeholder teams to define requirements, priorities, and delivery plans in an Agile environment Monitor, troubleshoot, and resolve platform issues; perform root-cause analysis and drive durable fixes. Supporting efficient system administration and troubleshooting to maintain application uptime and reliability. Improve resiliency, performance, and cost efficiency through design reviews and ongoing optimization Document designs, runbooks, and operational procedures to support reliable operations. Conducting peer code reviews to provide constructive feedback to improve code quality and maintain best practices. Coach and promote responsible use of AI-assisted engineering tools, including validation standards (peer review, testing, secure coding) Required qualifications, capabilities, and skills Bachelor’s or master’s degree in computer science, Engineering, or a related field, plus seven years of relevant experience Experience in design, development, debugging, and maintaining production grade Full stack application/services in a large-scale environment. Hands on experience in one of the programming languages – Java, Python, JavaScript/TypeScript. Proficiency in AWS services and patterns used to build resilient cloud platforms; Hands-on experience with Terraform in production environments (modules, state management, and safe change practices). Experience building or supporting CI/CD pipelines (for example, Jenkins) and using version control systems such as Git; leveraging Kubernetes and Docker for creating, testing, and deploying runtime environments. Experience designing and building Web Frameworks such as Spring boot, MVC and REST APIs and service integrations. creating user interfaces using React and internal UI toolkit libraries Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices Working knowledge of database technologies (relational and non-relational) such as Oracle, PostgreSQL, MySQL, DynamoDB etc. Experience in Distributed Database systems to manage and process large datasets efficiently to support advanced analytics and business intelligence. Creating and extracting data from databases using SQL queries, PL/SQL stored procedures. Experience delivering solutions using an Agile software development lifecycle. Experience monitoring and operating cloud services, including incident response and root-cause analysis. Experience implementing fault-tolerant, high-availability systems in complex environments. Experience using AI-assisted engineering tools with the ability to validate outputs for correctness, performance, and security, and to handle sensitive data appropriately Preferred qualifications, capabilities, and skills AWS Certified Developer and/or AWS Certified Solutions Architect (or equivalent) Experience with Amazon Connect or other cloud contact center platforms Experience with telephony and real-time communications and (for example, Web Real-Time Communication (WebRTC)) integrated application development. Familiarity with Jira, Confluence,