Software Engineer III - Cloud Engineering Acceleration

Job Responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems

Creates secure and high-quality production code, and reviews, debugs, and maintains code written by others

Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness

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 (e.g., CI/CD, infrastructure automation, operational workflows)

Produces architecture and design artifacts for platform services and complex applications, while being accountable for ensuring design constraints (security, resiliency, scalability, maintainability) are met by software code development

Participates in design reviews and technical discussions to evaluate solutions, strengthen quality, and support scalable delivery

Identifies opportunities to eliminate or automate remediation of recurring issues to improve operational stability across applications and systems

Collaborates with teammates and partner teams to evaluate and adopt tools and frameworks that improve developer experience and platform quality

Contributes to knowledge sharing (e.g., documentation, demos, brown bags, communities of practice) to support adoption of modern engineering approaches

Promotes a team culture of diversity, opportunity, inclusion, respect, continuous improvement, and shared learning

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and advanced applied experience

Hands-on practical experience in system design, application development, testing, and operational stability

Experience delivering production-grade solutions using one or more modern programming languages and frameworks/platforms such as Java, Spring, Go, Python, Terraform, and/or Kubernetes

Practical cloud-native experience building and operating services on at least one public cloud provider (Amazon Web Services, Microsoft Azure, or Google Cloud Platform)

Proficiency in automation and continuous delivery methods (CI/CD)

Working understanding of agile development practices, application resiliency, and security fundamentals

Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security

Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations

Strong communication skills with the ability to adapt messages for technical and non-technical audiences

Ability to evaluate technical solutions with a customer-focused mindset and understand how engineering decisions impact users and business outcomes

Preferred Qualifications, Capabilities, and Skills

Experience working in financial services or another highly regulated technology environment

Experience contributing to public cloud platform services, developer platforms, or shared engineering capabilities

Experience mentoring junior engineers or contributing to technical practice improvements within a team

Familiarity with responsible artificial intelligence use in engineering workflows, including secure handling of inputs and outputs

Experience improving developer experience, platform reliability, or operational efficiency at scale