Senior Software Engineer

As a Senior Software Engineer, you will own the end-to-end engineering lifecycle for key components and services — designing, coding, testing, deploying, and operating solutions that are secure, reliable, accessible, and maintainable. You will work independently within your project area, own architecture with minimal technical oversight, and use AI tools fluently across the development lifecycle to multiply your team's output. AI-native development: Use AI tools across the full SDLC in a disciplined way. Own the quality of AI-generated requirements, designs, and code - yours and your teammates' - and apply Responsible AI practices. Design and architecture: Lead design discussions for your project area, evaluate tradeoffs, and own architectural decisions with minimal oversight. Customer requirements: Partner with PM, and engineering to define requirements; ensure feedback loops on customer value and usage are in place. High-quality code: Write extensible, secure, performant code. Apply modern patterns including GenAI-assisted development. Drive code reviews and best practices at the product level. Testing and quality: Own the test strategy for your area. Improve the test suite and use AI tools for test automation. Dependencies and coordination: Identify cross-team dependencies, manage upstream/downstream impact, and resolve conflicts across teams. Planning: Drive your workgroup's project and release plans. Break work into a roadmap and coach others on estimation. Experimentation: Design and run experiments; interpret results to guide ship decisions. Deployment and velocity: Drive deployment automation toward zero-touch; strengthen CI/CD. Live site: Participate in on-call rotation. Use telemetry to diagnose, mitigate, and lead retrospectives. Drive metrics that improve reliability and customer impact. Security, privacy, accessibility: Apply security-as-code, threat modeling, and breach-drill practices. Ensure AI safety controls for production AI features. Meet privacy and accessibility standards. Leadership: Lead by example. Mentor engineers, raise the team's bar, and foster an inclusive culture. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Hands-on experience using AI-assisted development tools (e.g., GitHub Copilot, agentic coding workflows, GenAI-based code review and test generation) in a disciplined, production-grade way. Experience integrating AI capabilities (LLMs, agents, model-backed features) into production systems, including familiarity with Responsible AI principles and applying AI safety controls in production. Experience owning a feature area end-to-end, from design through deployment, monitoring, and on-call ownership. Experience designing and operating large-scale distributed systems in a cloud environment (e.g., Azure), including API and data model design, performance tuning, and cost optimization. Engineering fundamentals - data structures and algorithms, object-oriented and systems design, and building resilient services (reliability, availability, scalability). Experience with DevOps practices and tooling (CI/CD, infrastructure as code, monitoring and alerting, incident response) and a track record of driving toward zero-touch deployment. Experience designing and running experiments in production (A/B testing, feature flagging, controlled rollouts) and using results to drive product and engineering decisions. Experience building observable systems: designing telemetry, metrics, and dashboards that drive reliability, performance, and customer-impact decisions. Experience building secure software, including secure coding practices, threat modeling, premortems, and privacy/compliance considerations. Experience building accessible software and applying accessibility standards (e.g., WCAG) and privacy/compliance frameworks in production systems. Demonstrated technical leadership through design reviews, mentoring, and driving improvements to code quality and engineering processes. Experience collaborating in cross-functional teams and communicating technical concepts clearly to engineering, product, and executive audiences.