• Implement and optimize our AI SRE Teammate to meet the needs of our customers in production and pre-production environments. • Proactively monitor customer deployments (with Ciroos!) to ensure that our customers get the best out of the product. • Use Ciroos to uncover latent reliability issues (misconfigurations, deployment regressions, scaling) of customer environments. • Recommend best practices to customers for implementing the Ciroos AI SRE Teammate in their environment. • Plan, design, build, and maintain highly scalable, reliable, and efficient infrastructure for our AI SRE Teammate. • Serve as the customer’s technical advocate into engineering and product. • Conduct post-incident reviews to identify root causes and implement preventative measures. • Ensure security best practices are integrated into customer deployments. • Train SRE, Ops, and Platform teams at the customer on how to operate with Ciroos AI SRE Teammate. • Lead enterprise migrations onto Ciroos (e.g., replacing incumbent alerting/AIOps platforms such as BigPanda, Moogsoft, PagerDuty, Elastic, or Splunk), including replicating hundreds to thousands of existing correlation rules, running phased cutovers, and hitting hard customer go-live dates. • Design, build, and tune alert normalization and correlation policies—writing conditions and operators (IN / CONTAINS / REGEX), extracting fields from noisy sources (email, Jenkins, CI/CD), and choosing tailored playbooks over catch-all rules. • Integrate Ciroos with the customer’s operational stack—ticketing (e.g., ServiceNow bi-directional sync and field mapping), collaboration (Microsoft Teams / Slack), observability (Dynatrace, Quantum Metric, Databricks), and knowledge sources (GitHub, Confluence)—including any required app-marketplace certification. • Validate and continuously improve investigation quality—diagnosing query-conversion and enrichment errors, unblocking failed investigations, and tuning RCA accuracy so the AI SRE Teammate earns customer trust. • Stand up proactive health monitoring for customer deployments (e.g., real-time Slack status channels, SLA-driven alerts on missing metadata or ticket-creation failures) so issues are caught before the customer notices. • Own customer-facing communications and delivery artifacts—weekly executive status updates, SLA documents, escalation paths, and migration/scope-change tracking—and coordinate daily syncs with customer project leads. • Build long-term technical relationships with senior engineering leaders at customer organizations. • Own customer implementations end-to-end—from technical discovery and solution design through production cutover, UAT, go-live, hypercare, and post-launch stabilization—driving execution independently across customer, product, and engineering threads, and demonstrating MTTR reduction and elimination of manual toil. • Translate messy, ambiguous customer requirements into clear technical designs, milestones, trade-offs, and acceptance criteria, and keep execution truth legible by making blockers, risks, dependencies, and scope changes explicit early with clear owners and next steps. • Design and ship AI-powered investigation and remediation workflows with clear tool boundaries, guardrails, deterministic fallbacks, and human-in-the-loop controls—and define quality controls (versioning, grounding, evals, feedback loops) so the AI SRE Teammate stays trustworthy in production. • Ship reusable deployment modules, reference architectures, runbooks, and cutover plans (“golden paths”) that accelerate future customer work and raise delivery repeatability across accounts. • Own the value case: set impact hypotheses, baselines, and KPIs (e.g., MTTI/MTTR reduction, toil eliminated), run pre-/post-deployment measurement, and report ROI to executive sponsors. • Channel recurring field learnings into roadmap input and product hardening, especially where the same customer pain points show up across deployments. • Contribute to a culture of continuous learning and improvement within Ciroos.