Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
GitHub @ 4
Leadership @ 4
Communication @ 4
Slack @ 4
API @ 4
LLM @ 4
Microsoft 365 @ 4
Compliance @ 4
Salesforce @ 4
AI @ 4
Data Pipelines @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About Glean:
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business.
Role summary:
Glean is seeking a Connector TPM to build the "pipes" that feed the Glean Enterprise Graph. This role balances high-level product vision with deep technical constraints of distributed crawling, rate-limiting, and data security. You will own multi-quarter programs across high-impact connectors and the platform capabilities that power all connectors.
Responsibilities
- Own multi-quarter programs across highest-impact connectors (Microsoft 365, Google Workspace, Slack, Atlassian, Salesforce, GitHub, etc.) and platform capabilities.
- Work closely with tech leads and architects on system design, scalability, and reliability of the connectors stack.
- Design the operating model and technical roadmap to scale from dozens to hundreds of high-quality connectors without linear increases in operational burden.
- Lead design reviews to balance immediate customer needs with long-term platform scalability.
- Drive connector reliability by setting strict SLOs for data freshness and error rates; build telemetry and a root-cause culture to move from reactive fixes to proactive, high-uptime operations.
- Manage full connector lifecycle from intake and compliance to GTM launch.
Requirements
- 5+ years in TPM, PM, or Engineering, with 3+ years leading complex B2B SaaS or cloud infrastructure programs.
- Deep experience in large-scale distributed data pipelines and enterprise identity/security constraints.
- Experience with AI/ML, data pipelines, and API integrations.
- Proven ability to turn ambiguous problems into clear roadmaps, influence architectural designs with staff engineers, and lead operating rhythms such as design reviews and post-mortems.
- Excellent written and verbal communication; ability to write crisp technical program docs and present trade-offs to engineering and product leadership.
- A builder mindset and high ownership: willing to get into logs, dashboards, and traces; comfortable defining new processes and iterating quickly based on production learnings.
- Nice to have: first-hand experience building MCP Servers across various SaaS services.
Location & Office Policy
- This role is hybrid: 4 days a week in the San Francisco office.
Compensation & Benefits
- Base salary range: $198,000 - $235,500 annually.
- Compensation may include variable compensation, equity, and benefits depending on role and experience.
- Benefits include medical, vision, and dental coverage, generous time-off policy, 401(k) plan contributions, home office improvement stipend, annual education and wellness stipends, regular company events, and daily healthy lunches.
AI-First Mindset
- As part of the interview process, candidates will complete a brief AI-focused exercise or discussion to demonstrate how they think about, design, and use AI to drive impact in the role.
Global Data Privacy Notice
- Applicants are subject to Glean's privacy and applicant arbitration policies as outlined in the company's notices.