Glean AI Architect

Hi,

We have a very urgent requirement for Glean AI Architect. Please let me know if you or someone you know is interested.

Please see the job details below.

Job Title: Glean AI Architect

High Level details of these roles:

• Glean AI Architect — owns the overall Glean architecture, enterprise integration strategy, AI/agent solution design, governance, and technical leadership.
• Glean AI Developer/Engineer — builds the integrations, connectors, agents, workflows, APIs, and production-grade solutions under the Architect''s direction.

1. Glean AI Architect

Role: Glean AI Architect / Lead Glean Solution Architect

Experience: 10–15+ years overall; 3–5+ years in enterprise AI/GenAI, with significant hands-on Glean experience
Role Type: Senior Technical Lead / Architect
FDE/FDU Role: Technical Lead / Solution Architect

Role Summary

We are seeking an experienced Glean AI Architect to lead the architecture, design, implementation, and adoption of enterprise AI solutions using the Glean Work AI platform. The Architect will be responsible for translating business use cases into scalable Glean-based solutions encompassing enterprise search, RAG, AI assistants, AI agents, workflow automation, integrations, and agentic applications.

The Architect will lead the technical design for integrating Glean with enterprise applications, data sources, identity/security platforms, and AI/LLM ecosystems. The role will also establish architectural standards, reusable patterns, security/governance practices, and an enterprise roadmap for scaling Glean AI capabilities.

Glean currently provides APIs for search, chat and agents, an indexing/connector framework, Web SDK, agent tooling, MCP integrations, and permission-aware enterprise retrieval, making the Architect role broader than simply configuring Glean. ()

Key Responsibilities

Glean Architecture

• Define the enterprise Glean reference architecture, deployment model, integration patterns, and technical roadmap.
• Design Glean solutions spanning Search, Assistant, Agents, Apps, enterprise knowledge graph, RAG, and workflow automation.
• Assess business processes and identify opportunities for Glean-powered AI agents and automation.
• Establish reusable architecture patterns for enterprise-scale Glean implementations.
• Design solutions that leverage Glean''s permission-aware retrieval and enterprise context.

AI / Agent Architecture

• Design multi-step and multi-agent solutions using Glean Agents and agent orchestration.
• Define agent patterns for reasoning, retrieval, tool invocation, actions, human-in-the-loop approvals, and exception handling.
• Determine when to use Glean-native capabilities versus external frameworks such as LangChain, LangGraph, MCP, or custom applications.
• Design RAG and enterprise knowledge solutions using Glean Search/Chat APIs and knowledge graph capabilities.
• Establish agent evaluation, observability, quality, cost, and performance standards.

Enterprise Integration

• Architect integrations with applications such as:
• ServiceNow
• Salesforce
• Microsoft 365
• SharePoint
• Google Workspace
• Slack
• Jira/Confluence
• GitHub
• SAP/Oracle applications
• Data warehouses/lakes
• Custom enterprise applications
• Design API, webhook, MCP, connector and event-driven integration patterns.
• Define approaches for custom data ingestion and enterprise connectors.

Glean''s current platform supports 275+ native/MCP-based connectors and permission-aware access across enterprise applications, making connector and identity architecture a critical component of the role. ()

Security & Governance

• Define Glean security architecture and enterprise access-control patterns.
• Ensure source-system permissions are correctly reflected in Glean.
• Establish governance for AI agents, prompts, actions, models, data access, and human approvals.
• Partner with security, privacy, risk, and compliance teams.
• Define guardrails for responsible and secure enterprise AI adoption.

FDE/FDU Leadership

• Lead the Glean FDE/FDU technical team.
• Conduct technical discovery workshops with business and IT stakeholders.
• Translate business requirements into solution architecture and implementation backlogs.
• Review developer designs and code.
• Establish engineering standards, reusable components, and accelerators.
• Mentor Glean engineers and AI developers.
• Support PoCs, pilots, production implementations, and executive demonstrations.

Value & Adoption

• Define KPIs for AI adoption, productivity, automation, agent performance and business value.
• Establish an AI Agent Development Lifecycle (ADLC) covering ideation, design, development, testing, deployment, governance and continuous improvement. Glean introduced its enterprise ADLC framework in 2026 specifically to help enterprises scale agents with measurable business impact. ()
• Identify opportunities to convert successful pilots into reusable enterprise capabilities.

Required Skills

Must Have

• Strong hands-on Glean AI platform experience.
• Experience designing and implementing Glean enterprise solutions.
• Deep understanding of:
• Glean Search
• Glean Assistant
• Glean Agents
• Glean Apps
• Glean APIs
• Glean connectors/indexing
• Glean knowledge graph
• Glean Actions
• MCP
• Strong GenAI/LLM/RAG architecture experience.
• Experience with enterprise AI agents and agentic workflows.
• Strong API and integration architecture experience.
• Strong understanding of identity, RBAC/ABAC, data permissions and enterprise security.
• Experience with cloud platforms such as Azure, AWS or Google Cloud Platform.
• Strong Python and/or TypeScript understanding.
• Experience with REST APIs, JSON, OAuth/OIDC and event-driven architectures.

Preferred

• Glean certification or equivalent demonstrated expertise.
• Experience with LangChain/LangGraph, MCP, OpenAI/Azure OpenAI, Amazon Bedrock or Google Vertex AI.
• Experience implementing enterprise AI governance.
• Experience with ServiceNow, Salesforce, Jira, Slack, Microsoft 365 or similar enterprise ecosystems.
• Experience building production-grade AI agents.
• Experience with AI evaluation, observability, prompt engineering and LLMOps.
• Consulting/client-facing experience.

Key Deliverables

• Enterprise Glean Reference Architecture
• Glean Integration Architecture
• Glean Agent Architecture & Design Standards
• AI/Agent Use Case Assessment Framework
• Security & Governance Framework
• Glean Implementation Roadmap
• Reusable Glean accelerators/components
• Production-ready AI agent designs
• Technical standards and engineering playbook