Architect (Multi-skill) AI Transformation Core Team CPG

• ​​​​​​​Location: Cincinnati, OH


• ​​​​​​​Remote


• Domain: Consumer Goods Experience


• Grade: P7 / P8.

Own the end-to-end technical architecture for the Foundational AI Platform — agentic orchestration, MCP server design and MCP gateway integration, observability/SRE, ITSM/AIOps, and AI solutions targeting applications hosted on Azure and GCP. Drive joint architecture decisions with the Knowledge Fabric team, the client's AI platform teams, and the partner ecosystem.

Key responsibilities

Foundational AI Platform (own)

• Architect the agent orchestration layer — multi-agent topologies, planning/reasoning patterns, agent-to-agent communication, human-in-the-loop gates, fallback and recovery.


• Define the Cockpit / control plane — agent registry, version control, deployment, runtime configuration, policy enforcement, traceability dashboards.


• Define the Guardrails & Responsible AI architecture — PII redaction, content safety, jailbreak resistance, output validation, policy-as-code, model risk management.


• Design the agent observability and evaluation architecture — tracing, token/cost telemetry, golden-set regression suites, drift detection, A/B harnesses.


• Architect Agent & Copilot Starter Kits — reusable templates spanning AIOps (triage, incident commander, RCA, resolution, SOP, postmortem, change-impact), engineering productivity, and domain-specific copilots.

MCP server + MCP gateway (own — key area)

• MCP server reference design (Resources, Tools, Prompts, Sampling) and an implementation playbook for service-line teams.


• MCP gateway: discovery, registry, routing, transport bridging (stdio / Streamable HTTP / SSE), multi-tenancy.


• AuthN/AuthZ via OAuth 2.1, OIDC,  On behalf of execution

Knowledge Fabric collaboration (consume, not build)

• Define retrieval, schema, and SLA contracts with the KF team. Integrate GraphRAG outputs into agents; feedback quality signals.

AI solutions on Azure + GCP application estates

• Architect agentic and RAG solutions using Azure (Azure OpenAI, AI Foundry, AI Search, Cosmos DB, AKS) and GCP (Vertex AI, Gemini, BigQuery, GKE) services native to the apps being served.


• Cross-cloud connectivity, hybrid retrieval, model/inference routing, secrets and identity propagation across estates.

Engineering excellence and leadership

• Architecture reviews, design standards, mentoring pods across business units; co-own roadmap with the joint PMO; drive AI-native SDLC adoption (spec-driven frameworks, AI coding assistants).

Must-have

• 10+ years in architecture; 3+ years experience in GenAI/agentic systems (2+ years live production experience).


• Hands-on MCP — server implementation and gateway integration.


• Agent frameworks (LangGraph, AutoGen, Semantic Kernel or equivalent), RAG/GraphRAG, evals, guardrails.


• Azure and GCP AI/data stacks; Kubernetes; IaC.


• Strong API, security (OAuth 2.1/OIDC/mTLS), and observability fundamentals.

Good-to-have

• AIOps / ITSM integration (ServiceNow, observability platforms).


• Spec-driven dev (BMAD, Spec Kit, OpenSpec) and AI coding assistants.


• Multi-vendor delivery in regulated enterprises.