• Serve as the technical lead for modernizing legacy enterprise applications into a scalable, cloud-ready architecture • Define technical direction, architecture standards, and engineering best practices for the team • Lead design sessions and architecture reviews; document technical decisions and solutions • Guide decomposition of monolithic systems into well-scoped, maintainable microservices • Design and implement backend services and RESTful APIs using modern frameworks and patterns • Provide technical leadership for frontend development and ensure clean API contracts • Lead secure authentication and authorization approaches in partnership with security stakeholders • Promote CI/CD automation, infrastructure-aware design, and production readiness (logging, monitoring, resiliency) • Balance technical debt reduction with delivery timelines and operational risk • Mentor engineers through code reviews, technical coaching, and day-to-day guidance • Partner closely with product, operations, and program stakeholders to deliver high-quality outcomes • Identify risks early and recommend mitigation strategies to keep delivery on track

• Building and maintaining fullstack product features from frontend to backend. • Considering user experience, workflows, and clarity when implementing solutions. • Contributing meaningfully across UI, APIs, and services. • Shipping small, well-scoped changes frequently. • Working closely with Product, Design, and Engineering peers.

• Designing and building AI-powered features and tooling used by customers and internal teams. • Owning fullstack solutions that include frontend, backend, and AI components. • Establishing patterns, guardrails, and examples that other engineers can safely build on. • Ensuring AI features behave predictably in production, including fallback behavior and observability. • Working closely with Product, Design, and Engineering peers to scope and deliver AI-driven solutions.

• Design and maintain network data models within DCIM platform that serve as the authoritative source of truth for all downstream automation. • Build intent-based cutsheet automation that generates deployment artifacts (cable matrices, rack elevations, port mappings) directly from network models. • Develop config generation pipelines that render device configurations from templates and network model data. • Create device validation and health check tooling that automates the deployment lifecycle — from bootstrap through validation to production handoff. • Build automation frameworks for network provisioning, including ZTP workflows and device onboarding. • Collaborate with cross-functional partners (DCIM SWE, ICT, Deployment teams) to ensure physical and logical artifacts align throughout the deployment process. • Contribute to the design and architecture of network automation systems, identifying opportunities to reduce manual effort and improve reliability.