• Define and drive the technical vision for DevOps practices across the organization • Lead architecture decisions for infrastructure, CI/CD pipelines, and cloud resources • Serve as a technical escalation point for complex infrastructure challenges • Conduct design reviews and provide guidance on reliability, security, and scalability • Design, build, and maintain cloud infrastructure on Google Cloud Platform using Terraform • Own and improve CI/CD pipelines to enable fast, safe deployments • Implement and maintain monitoring, alerting, and observability systems • Drive incident response processes and lead post-mortems to improve system resilience • Partner with product engineering teams to understand their infrastructure needs and translate them into scalable solutions • Work closely with Security to implement and maintain compliance and security best practices • Collaborate with Product and Engineering leadership on capacity planning and technical roadmaps • Mentor and coach DevOps engineers, fostering growth and technical development • Establish and document DevOps standards, runbooks, and best practices • Champion a culture of reliability, automation, and continuous improvement

• Deploy and manage cloud infrastructure across all three clouds using Terraform IaC • Architect, build and maintain reliable CI/CD pipelines in Github Actions and ArgoCD • Build and maintain tests to provide observability and alerting coverage across our infrastructure • Contribute to decisions around our departmental roadmap and project priorities • Analyze and architect a unified platform to support additional acquired tech stacks.

• Develop and maintain observability solutions using platforms like Datadog, Prometheus and Grafana • Take a leading role in incident management, including coordinating response efforts, troubleshooting issues, and identifying follow-up actions • Partner with product engineering teams to architect reliable systems, recover from incidents, and learn from mistakes • Work with teams to implement and maintain SLOs, monitoring, and alerting strategies that ensure reliability at scale • Design and implement automation and support tooling to improve system resilience, maintain operational safety and reduce operational overhead • Lead the development and maintenance of runbooks, alert definitions, and incident response procedures • Participate in on-call rotations to provide 24/7 support for critical production systems

• Own the reliability, availability, and failover behavior of the centralized planning system in production, with a focus on high-availability architectures across servers and clusters. • Design and implement leader election, health checks, heartbeat protocols, and controlled failover/hand-off when instances fail or become partitioned. • Define and build state continuity mechanisms so backup instances can take over from recent state (tickets/trips/journeys, vehicle/site state, restrictions) instead of cold-starting. • Engineer restart-safe, idempotent workflows for trip/ticket handling and routing decisions so replays, retries, and partial failures do not cause double assignment or missing states. • Extend and refine recovery behaviors, ensuring the system gets to a safe state first and then resumes normal operations in a controlled, observable way. • Expand and maintain observability: logs, metrics, traces, dashboards, and alerts for key service indicators (latency, backlog, heartbeats, failover time, instance divergence). • Harden configuration, pipelines, and deployments for the system and related services, including validation of config changes and safe rollout strategies (rolling, blue-green, canary). • Design and maintain automated test and robustness suites, including scenario-based, stress, fault-injection/chaos, and long-running burn-in tests, and use results to drive hardening work. • Apply safety-critical, requirements-driven reasoning (including FMEA-style analyses) to functional changes, documenting assumptions and guarantees. • Collaborate with algorithm developers, Autonomy, Test Ops, and Product to align robustness and failover behavior with algorithmic guarantees, operational procedures, and milestones, and take long-term ownership of production health.