Used Tools & Technologies
Not specified
Required 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 @ 3
Go @ 5
Python @ 5
SQL @ 3
Java @ 5
GitHub @ 3
NoSQL @ 3
Distributed Systems @ 3
Jira @ 3
ServiceNow @ 3
Slack @ 3
API @ 3
LLM @ 3
Microsoft 365 @ 3
Salesforce @ 3
Observability @ 3
AI @ 3
Data Pipelines @ 3
- 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
Glean is the Work AI platform that helps everyone work smarter with AI. The Data Foundations team owns the end-to-end data ingestion and management layer powering Glean's Search, AI Assistant, and Agent products across thousands of enterprise apps and billions of documents. Your work will determine the quality, freshness, and trustworthiness of the knowledge every Glean user interacts with daily.
Responsibilities
- Build and scale connectors to a wide variety of SaaS and on-prem systems (Google Workspace, Microsoft 365, Slack, Salesforce, Jira, ServiceNow, GitHub, etc.).
- Handle full syncs and low-latency incremental updates via webhooks/APIs, including rate-limiting and complex authentication flows.
- Build advanced datasource capabilities such as actions, live-fetch, and query language support.
- Transform raw, unstructured enterprise content into rich, structured, permission-aware representations optimized for search and LLM reasoning.
- Design document schemas and enrichment pipelines (entity extraction, access-graph propagation, redactions, etc.).
- Expand AI product capabilities via deep integrations to automate tasks, perform complex grounded queries, and enhance indexed corpora with live data.
- Own end-to-end correctness, freshness, and performance for petabyte-scale data flows.
- Solve problems in ordering, idempotency, exactly-once processing, backpressure, and retries across distributed queues, workers, and storage.
- Preserve fine-grained ACLs, deletions, and sensitivity constraints to ensure AI answers respect permissions.
- Partner with Search Serving, Product, Platforms, and Security teams to define how enterprise context is exposed to LLMs and agents.
- Improve observability, alerting, and automation to onboard larger customers and more data sources with confidence.
Requirements
- 3+ years building production backend or data infrastructure systems using languages such as Java, Go, C++, or Python.
- Hands-on experience with distributed systems, data pipelines, queues, and large-scale storage (SQL/NoSQL).
- Experience designing for SLOs, error budgets, failure modes, and correctness guarantees.
- Comfortable with strict consistency and permission-modeling challenges.
- Prior work on enterprise connectors, search/indexing, information retrieval, or security-sensitive systems is a strong plus.
- Power user of LLMs and AI tools in your own workflow.
Location
- This role is hybrid: 4 days a week in one of Glean's San Francisco Bay Area offices.
Compensation & Benefits
- Base salary range: $140,000 - $265,000 annually. Compensation offered will depend on location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
- Benefits include Medical, Vision, and Dental coverage, generous time-off policy, opportunity to contribute to a 401(k) plan, a home office improvement stipend, annual education and wellness stipends, regular company events, and daily lunches.