Customer Engineer
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- Diagnose the workload, define success + shape the target platform architecture
- Own reliability, adoption + technical leadership from validation through production
Benchmark: Google Cloud Customer Engineer + Cognizant AI Customer Engineer (current Sep 2026) Market refresh: customer-facing cloud/platform architecture, workload discovery, systems design, workshops, debugging and prototypes; APIs/data integration; identity/security; AI agents/RAG where relevant; PoCs/MVPs; migration and production readiness; reliability, adoption, executive guidance and sales-to-delivery continuity.
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Diagnose the workload, define success + shape the target platform architecture
Customer discovery, workload assessment + outcomes
Coverage: Product Discovery / Use-Case Scoping / Technical Workshops
Cloud architecture, APIs + system design
Coverage: Cloud Architecture / Well-Architected Systems / API Design
Prototyping, APIs + AI/data integration
Coverage: Python / FastAPI / AI Agents / Integration Prototyping
Identity, security + production troubleshooting
Coverage: IAM / Zero Trust / Debugging / Production Readiness
Own reliability, adoption + technical leadership from validation through production
Reliability, migration + operational adoption
Coverage: SLOs / Incident Readiness / Migration / Change Adoption
Evaluation, customer value + executive technical guidance
Coverage: Evaluation / Business Value / Executive Communication / Delivery Handoff
Role-Readiness Proof / Capstone
Act as the technical owner for a strategic customer workload from discovery through production readiness. Run a workload/use-case workshop; define measurable success and a target cloud architecture; build a working API/data or AI-enabled prototype; integrate identity and security; test reliability and failure behavior; document migration and deployment steps; create SLOs, observability and a runbook; deliver a technical deep dive plus executive value narrative; then hand off to delivery with adoption milestones and a field-feedback backlog.
Proof Rubric
- Show trusted-advisor behavior backed by engineering evidence: accurate discovery
- defensible architecture
- hands-on prototype and debugging
- secure identity/data boundaries
- measurable quality, latency and reliability
- explicit migration/operational risks
- clear executive communication
- smooth sales-to-delivery continuity
- adoption measures
- and product/engineering feedback grounded in real customer friction rather than anecdotes