ServiceNow AI Engineer / Agentic AI Platform Engineer
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- Design high-value enterprise agent workflows and build them in ServiceNow AI Agent Studio
- Ground agents in enterprise context and connect actions across systems
- Govern, evaluate and operate production agent ecosystems across ServiceNow and external tools
Benchmark: ServiceNow AI Engineering & Delivery + current Staff/Senior Staff Agentic AI and AI Control Tower engineering signals (current Sep 2026). Market refresh: AI Agent Studio; Now Assist; agentic workflows and orchestration; Skill Kit; AI Search/RAG; Workflow Data Fabric; Integration Hub; MCP/A2A; AI Gateway/Control Tower; evals, guardrails, observability and production reliability.
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Enrichment
Design high-value enterprise agent workflows and build them in ServiceNow AI Agent Studio
Agentic workflow architecture + use-case design
Coverage: ServiceNow AI Agents / Agentic Workflows / Orchestrator / Worker Agents / Outcome Design / Process Evidence
AI Agent Studio, prompts + tool construction
Coverage: AI Agent Studio / Prompt Engineering / Skills / Flows / Scripts / Knowledge / Human Approvals
Ground agents in enterprise context and connect actions across systems
Now Assist Skill Kit, Integration Hub + reusable tools
Coverage: Now Assist Skill Kit / Integration Hub / Subflows / APIs / Tool Design / External Actions
Workflow Data Fabric, AI Search + enterprise grounding
Coverage: Workflow Data Fabric / Zero Copy / AI Search / RAG / Knowledge Graph / Enterprise Context
Govern, evaluate and operate production agent ecosystems across ServiceNow and external tools
Agent evals, guardrails + production readiness
Coverage: Now Assist Data Kit / Agent Evals / Ground Truth / Guardian / Privacy / Prompt Injection / Human-in-the-Loop
MCP/A2A governance, AI Gateway + Control Tower observability
Coverage: AI Gateway / AI Control Tower / MCP / A2A / AI Agent Fabric / Tool Governance / Security / Observability
Role-Readiness Proof / Capstone
Design, build and operate a production ServiceNow agentic workflow for a real enterprise process. Use process evidence to select the use case and define measurable outcomes; build the workflow in AI Agent Studio with a clear orchestrator and scoped worker agents; implement prompts plus at least two tools using flows, scripts, Skill Kit, Integration Hub or APIs; ground decisions in governed context through AI Search, Knowledge Graph or Workflow Data Fabric; connect one external capability through MCP or A2A where justified; enforce identity, ACL/data controls, privacy/Guardian controls and human approvals; create ground-truth evals and tool-use tests; route MCP traffic through AI Gateway with governance and observability; run failure, prompt-injection and data-leakage drills; deploy with KPI monitoring and publish a runbook plus measured business impact.
Proof Rubric
- Prove evidence-backed use-case choice
- clear agent and orchestrator boundaries
- precise prompts and robust tool contracts
- grounded retrieval and data-context quality
- correct ServiceNow ACL/permission behavior
- safe external MCP/A2A connectivity
- reproducible evals and ground-truth results
- guardrail/privacy effectiveness
- human escalation where required
- diagnosable traces and gateway observability
- reliable workflow recovery
- measurable task completion, cycle-time or experience impact
- and documented iteration based on test or production evidence