Software Engineer 3

Job Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• 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.
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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.
• Deep knowledge of one or more areas of SRE such as hardware, networking terminology, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
• Deep knowledge of at least one specific messaging/streaming technology (ex. Kafka, Kinesis) and one programming/scripting language (Java, Python, Unix Shell Scripting)
• Drives to continue to develop technical and cross-functional knowledge outside of the product
• Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in public and private clouds (ex. AWS, Cloud Foundry, Kubernetes
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Required qualifications, capabilities, and skills

• Significant programming background in any applicable language, with familiarity in Linux and development using Linux platforms.
• Knowledge and certifications in Kubernetes, Azure, GCP, Terraform, and AWS, along with experience in public cloud platforms like AWS, GCP, and Azure.
• Proficiency in automation technologies such as Puppet and Terraform, as well as database platforms and SQL.
• Experience with CICD processes and technologies (e.g., Jenkins, Jira, Git) and authentication and authorization technologies (e.g., OAuth, Kerberos).