• Write, test, and ship production-quality code regularly, with a focus on maintainability, performance, reliability, and business impact. • Use AI-assisted development tools responsibly to accelerate development, debugging, testing, and code quality. • Build and maintain backend application logic, APIs, service objects, data models, background jobs, and integrations. • Begin to take ownership over feature-level or component-level implementation, including delivery and post-release support. • Collaborate with product managers, designers, and fellow engineers to translate business goals into reliable technical solutions. • Troubleshoot and debug production issues, participating in support escalations as needed. • Regularly estimate tasks and deliver within those estimates with increasing accuracy and independence. • Show judgment in prioritizing tasks and understanding trade-offs.

• Building powerful, yet easy-to-use next generation web applications to achieve consistent user experience across our multiple applications • Contributing to a library of common components and development tooling • Utilizing pixel-perfect layout skills and hand coding of both simple and complex cross-browser and cross-platform solutions • Contributing to all aspects of the project lifecycle: define, design, develop, and test

• Lead, coach, and scale a high-performing team of engineers and scientists; initially as a line manager, with scope to manage managers as the organization grows. • Own delivery of agentic AI systems from ambiguous customer need through prototype, production deployment, evaluation, and iteration. • Stay technically hands-on through architecture reviews, build/buy decisions, agentic workflow design, eval strategy, and urgent customer-critical problem solving. • Partner with the Director of Product, Director of UX, and customer-facing teams to translate customer workflows into clear technical roadmaps. • Build operating mechanisms that help the team move fast without unnecessary process: crisp priorities, clear ownership, fast feedback loops, and disciplined execution. • Raise the engineering bar for reliability, observability, security, compliance, and deployment quality in high-consequence enterprise environments. • Recruit, develop, and retain exceptional technical talent; create a culture where engineers and scientists do their best work. • Model RD’s tenets: continuously delight customers, remove bottlenecks, disagree and commit, take ownership of every problem, prototype rapidly, and stay at the leading edge.

• Design and deliver intelligent systems that handle everything from alarm correlation to zero-touch remediation. • Build pipelines for real-time structured datasets using Apache Flink or Spark Streaming. • Collaborate with Network SMEs to identify AI opportunities in alarm fatigue reduction and root cause analysis. • Implement large-scale telemetry processing using Pyspark and Databricks. • Deploy and monitor models in production using SageMaker, ensuring robustness for global-scale operations.