Software Engineer, Data Foundations
GleanSan Francisco Bay Area$140k – $265kPosted 7 April 2026
Job Description
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 - without vendor lock-in or costly implementation cycles.
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the Role:
We are looking for a Software Engineer to join Glean’s Data Foundations team — the group that 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 directly determine the quality, freshness, and trustworthiness of the knowledge that every Glean user interacts with every day.
You will work on:
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, low-latency incremental updates via webhooks/APIs, rate-limiting, and complex authentication flows.
Build advanced capabilities in datasources like 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 the capabilities of AI products through deep integrations that allow us to automate tasks, perform complex queries grounded in enterprise data, and enhance our indexed corpus with live data.
Own end-to-end correctness, freshness, and performance for petabyte-scale data flows.
Solve hard problems in ordering, idempotency, exactly-once processing, backpressure, and retries across distributed queues, workers, and storage.
Preserve fine-grained ACLs, deletions, and sensitivity constraints so AI answers are always grounded in what users are actually allowed to see.
Partner closely with Search Serving, Product, Platforms, and Security teams to define how enterprise context is exposed to LLMs and agents.
Continuously improve observability, alerting, and automation to onboard larger customers and more data sources with c ... (truncated, view full listing at source)
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