• 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 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
• AWS architecture & core services — hands-on experience building in AWS with services like VPC, EKS, IAM, S3, Lambda, CloudWatch, KMS, ALB/NLB, Auto Scaling.
• Hands-on experience deploying and operating containerized workloads on AWS ECS and/or EKS, including service orchestration, networking/load balancing, IAM/security, autoscaling, and troubleshooting in production.
• AWS networking — VPC design (subnets, route tables, NAT/IGW), security groups/NACLs, Private Link/VPC endpoints, hybrid connectivity concepts (VPN/Direct Connect), DNS (Route 53).
• Terraform — authoring reusable modules, workspaces, remote state/backends, state management, imports, lifecycle/meta-arguments, dependency design, and troubleshooting plans/applies.
• 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; ability to guide peers on safe and effective usage within team practices.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Familiarity with messaging systems like Confluent Kafka, AWS MSK and related components such as Kafka streams, Connect, Schema registry.
• Familiarity with streaming pipeline systems like Confluent Kafka, AWS MSK and related components such as Kafka streams, Connect, Schema registry.

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