Keywords: MCP · Agent-to-Agent Orchestration · Enterprise Connectors · Google Workspace · Microsoft 365 · CI/CD · Python/Go
About the Role
You own how agents talk to each other and to the rest of the enterprise. On the Governance Control Tower pod, that means building and maintaining the MCP servers and orchestration protocols that let agents call tools and each other safely, wiring enterprise connectors — Google Workspace, Microsoft 365, vendor-managed MCP servers — into the retrieval layer, and making sure every integration point is wired into AssureAI's evaluation harness so nothing ships ungoverned.
What You'll Own
- Build and operate MCP servers — not just consume them — for agent-to-agent and agent-to-tool communication.
- Integrate enterprise connectors across Google Workspace, Microsoft 365, and vendor-managed MCP servers into the federated retrieval layer.
- Own the CI/CD wiring that runs AssureAI's evaluators automatically on every agent or connector commit.
- Maintain orchestration protocols — routing, tool use, hand-offs — for the shared top-level agent layer the GCP AI Architect designs.
- Debug cross-agent and cross-system integration issues as the agent roster grows.
- Partner with the AI Engineers to onboard new agents' tool and connector dependencies cleanly.
What We're Looking For
- 5+ years building integrations or orchestration for distributed/service-oriented systems, with 1–2+ years specifically on agentic AI / LLM tool-use architectures.
- Direct experience with MCP — building servers, not only consuming them.
- Experience with enterprise connector work (Google Workspace, Microsoft 365 APIs, or comparable), including auth and entitlement-aware access.
- Experience with the Google ADK agent runtime specifically.
- Familiarity with AssureAI or comparable evaluation tooling from the integration side, not just the eval side.
- Prior work on API gateways (Apigee or similar) in a governed or regulated environment.
What Success Looks Like
By month two: every agent's tool and connector calls route through a common, monitored MCP layer rather than one-off integrations.
Gemini – Integration Specialist
1 position
Keywords: MCP · Agent-to-Agent Orchestration · Enterprise Connectors · Google Workspace · Microsoft 365 · CI/CD · Python/Go
About the Role
You own how agents talk to each other and to the rest of the enterprise. On the Governance Control Tower pod, that means building and maintaining the MCP servers and orchestration protocols that let agents call tools and each other safely, wiring enterprise connectors — Google Workspace, Microsoft 365, vendor-managed MCP servers — into the retrieval layer, and making sure every integration point is wired into AssureAI's evaluation harness so nothing ships ungoverned.
What You'll Own
- Build and operate MCP servers — not just consume them — for agent-to-agent and agent-to-tool communication.
- Integrate enterprise connectors across Google Workspace, Microsoft 365, and vendor-managed MCP servers into the federated retrieval layer.
- Own the CI/CD wiring that runs AssureAI's evaluators automatically on every agent or connector commit.
- Maintain orchestration protocols — routing, tool use, hand-offs — for the shared top-level agent layer the GCP AI Architect designs.
- Debug cross-agent and cross-system integration issues as the agent roster grows.
- Partner with the AI Engineers to onboard new agents' tool and connector dependencies cleanly.
What We're Looking For
- 5+ years building integrations or orchestration for distributed/service-oriented systems, with 1–2+ years specifically on agentic AI / LLM tool-use architectures.
- Direct experience with MCP — building servers, not only consuming them.
- Experience with enterprise connector work (Google Workspace, Microsoft 365 APIs, or comparable), including auth and entitlement-aware access.
- Working familiarity with Google Gemini Enterprise / ADK, or a comparable enterprise agent platform.
Nice to Have
- Experience with the Google ADK agent runtime specifically.
- Familiarity with AssureAI or comparable evaluation tooling from the integration side, not just the eval side.
- Prior work on API gateways (Apigee or similar) in a governed or regulated environment.
What Success Looks Like
By month two: every agent's tool and connector calls route through a common, monitored MCP layer rather than one-off integrations.
Gemini – Integration Specialist
1 position
Keywords: MCP · Agent-to-Agent Orchestration · Enterprise Connectors · Google Workspace · Microsoft 365 · CI/CD · Python/Go
About the Role
You own how agents talk to each other and to the rest of the enterprise. On the Governance Control Tower pod, that means building and maintaining the MCP servers and orchestration protocols that let agents call tools and each other safely, wiring enterprise connectors — Google Workspace, Microsoft 365, vendor-managed MCP servers — into the retrieval layer, and making sure every integration point is wired into AssureAI's evaluation harness so nothing ships ungoverned.
What You'll Own
- Build and operate MCP servers — not just consume them — for agent-to-agent and agent-to-tool communication.
- Integrate enterprise connectors across Google Workspace, Microsoft 365, and vendor-managed MCP servers into the federated retrieval layer.
- Own the CI/CD wiring that runs AssureAI's evaluators automatically on every agent or connector commit.
- Maintain orchestration protocols — routing, tool use, hand-offs — for the shared top-level agent layer the GCP AI Architect designs.
- Debug cross-agent and cross-system integration issues as the agent roster grows.
- Partner with the AI Engineers to onboard new agents' tool and connector dependencies cleanly.
What We're Looking For
- 5+ years building integrations or orchestration for distributed/service-oriented systems, with 1–2+ years specifically on agentic AI / LLM tool-use architectures.
- Direct experience with MCP — building servers, not only consuming them.
- Experience with enterprise connector work (Google Workspace, Microsoft 365 APIs, or comparable), including auth and entitlement-aware access.
