Software Development: Write clean, maintainable, and efficient code for various software applications and systems. Technical Leadership: Contribute to the design, development, and deployment of complex software applications and systems, ensuring they meet high standards of quality and performance. Project Management: Manage execution and delivery of features and projects, negotiating project priorities and deadlines, ensuring successful and timely completion with quality. Architectural Design: Participate in design reviews with peers and stakeholders and in the architectural design of new features and systems, ensuring scalability, reliability, and maintainability. Code Review: Diligently review code developed by other engineers; provide feedback and maintain a high bar of technical excellence ensuring adherence to coding guidelines, observability, and unit test coverage. Testing: Build testable software, define tests, participate in the testing process, automate tests using tools (e.g., JUnit, Selenium, Pytest) and design patterns leveraging the test automation pyramid. Service Health and Quality: Maintain the health and quality of services and incidents, proactively identifying and resolving issues. Utilize service health indicators and telemetry; conduct root cause analysis and drive preventive measures. DevOps Model: Take full ownership from requirements through design, develop, test, deploy, and maintain in a DevOps model. AI Feature Ownership: Design, build, and integrate AI/ML capabilities into production software systems; evaluate AI architectural tradeoffs and select appropriate approaches for given product features and use cases. Documentation: Properly document new features, enhancements, or fixes to the product, contributing to training materials. Mentorship: Guide and mentor P1/P2 engineers on engineering best practices, design thinking, and effective use of AI-augmented development workflows. Bachelor's degree in computer science, Engineering, or a related technical field, or equivalent practical experience. 4+ years of professional software development experience. Deep expertise in one or more programming languages such as C#, .NET and JavaScript. Extensive experience with software development practices and design patterns. Proficiency with version control systems (e.g., GitHub) and work tracking systems (e.g., JIRA). Understanding of cloud technologies and DevOps principles. Hands-on experience designing, building, or integrating AI/ML capabilities into production software systems; ability to evaluate AI architectural tradeoffs and select appropriate approaches for product use cases. Proficient use of AI-assisted development tools (e.g., Claude, GitHub Copilot, Cursor) to accelerate design, implementation, and code review cycles; ability to validate and improve AI-generated outputs against quality, security, and performance standards. Experience with prompt engineering techniques applied to real product features, customer-facing experiences, or engineering tooling. Experience with cloud platforms like Azure, AWS, or GCP. Familiarity with CI/CD pipelines and automation tools. Experience with test automation frameworks and tools. Knowledge of agile development methodologies. Familiarity with developing accessible technologies. Excellent communication and interpersonal skills.
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