TechInsights

DevOps Engineer

• Own SLOs, SLIs, and error budgets for all production services; drive error budget discipline across engineering
• Design reliability patterns for AI agent pipelines: LLM observability, tool-use tracking, failure detection, and graceful degradation
• Architect for blast radius containment — agent failures must have bounded customer impact through isolation, circuit breaking, and rapid recovery
• Mature our Canada Central/West active-active architecture toward 24-hour RTO with full regional failover
• Lead incident response and post-incident reviews that produce durable fixes; maintain DR procedures through regular testing
• Serve as the primary reliability liaison to Software and AI Engineering, translating requirements into actionable standards
• Partner with AI Engineering on compute provisioning, model serving, inference latency, and workload isolation
• Own CI/CD pipeline strategy (Bitbucket Pipelines, GitHub Actions) — set standards, optimize deployment frequency, and ensure teams can ship confidently
• Drive IDP adoption and enable teams on SRE practices: on-call readiness, SLO definition, runbook development, and self-service tooling
• Represent reliability in architectural discussions; surface risk before it's committed to design
• Own the service catalog — a living inventory of all services, AI agents, dependencies, ownership, and SLOs
• Operate Datadog as the single pane of glass for service health, infrastructure, and agentic pipeline telemetry
• Extend observability to AI workloads: LLM latency, token consumption, agent completion rates, and pipeline throughput
• Build golden path templates in Backstage and/or Atlassian Compass so teams ship reliably without routine SRE involvement
• Apply AIOps in Datadog to automate anomaly detection, incident triage, and remediation recommendations
• Own infrastructure as code via Terraform and GitOps; enforce IaC policy in partnership with Trust Assurance
• Own FinOps visibility into AWS cost segments; model cloud cost impact as AI/ML workloads scale
• Formally mentor junior and intermediate SRE engineers, with accountability for their technical growth and career progression
• Build AI-assisted automation to progressively reduce toil and scale the team's operational capacity

Senior Site Reliability Engineer

Analyst

• Monitor publicly available financial releases and announcements from key semiconductor manufacturers and capital equipment companies
• Maintain and update the SME Company Analysis and Equipment Analysis spreadsheets
• Cross-correlate financial data against SME model results to validate and calibrate models across capacity, capital spending, depreciation, cost, and margin data
• Assist the President and Director of SME in maintaining and updating the SME models
• Follow key semiconductor manufacturer announcements and financial releases

Senior Analyst, Semiconductor Manufacturing Economics

• Own SLOs, SLIs, and error budgets for all production services
• Drive error budget discipline across engineering
• Design reliability patterns for AI agent pipelines
• Lead incident response and post-incident reviews that produce durable fixes
• Serve as the primary reliability liaison to Software and AI Engineering
• Own CI/CD pipeline strategy
• Own the service catalog
• Operate Datadog as the single pane of glass for service health