Customer Support & Service AI Consultant
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- Design the support system and ground answers in trusted customer knowledge
- Deploy agentic triage, routing and human escalation for complex issues
- Measure quality, reliability and customer outcomes while closing the feedback loop
Benchmark: OpenAI support automation, support engineering and agentic-operations signals (current Sep 2026) Design the support system and ground answers in trusted customer knowledge Deploy agentic triage, routing and human escalation for complex issues Measure quality, reliability and customer outcomes while closing the feedback loop Case lifecycle, customer context and service workflow design
Who’s Hiring Right Now
US openings posted in the last 7 days at OpenAI — this role’s own benchmark employers — refreshed daily, as of 2026-11-01. Pulled directly from each company’s public job board; not exhaustive, and postings close fast — worth confirming the details on the employer’s own site before applying.
Design the support system and ground answers in trusted customer knowledge
Case lifecycle, customer context and service workflow design
Coverage: Operations Management & Operating Models
Knowledge retrieval, RAG and permission-aware grounding
Coverage: Retrieval-Augmented Generation (RAG)
Deploy agentic triage, routing and human escalation for complex issues
Support agents, tool use and seamless human handoff
Coverage: AI Agents & Tool Use
Intent classification, routing, prioritization and escalation
Coverage: Natural Language Processing & Workflow Automation
Measure quality, reliability and customer outcomes while closing the feedback loop
Answer quality, CSAT, deflection, resolution and service-level metrics
Coverage: AI Evals, KPIs & Support Analytics
Security, observability, incident learning and product feedback loops
Coverage: AI Security, Monitoring & Reliability
Role-Readiness Proof / Capstone
Design a production support system with trusted-knowledge RAG, case triage, tool-using agent assist, automated routing and explicit human escalation. Build evals for answer quality and resolution, instrument CSAT/deflection/SLA metrics, add access controls and observability, and create a feedback loop that converts recurring issues into product or documentation improvements.
Proof Rubric
- Explain the service workflow and knowledge boundaries clearly
- apply retrieval, routing and escalation to realistic cases
- compare self-service, agent-assist and human handoff
- show eval, CSAT, SLA, reliability and security evidence
- quantify deflection, resolution time or customer-impact improvement