Software Engineer (Data Foundations)

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

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

Reliability & Distributed Systems

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 confidence- 3+ years building production backend or data infrastructure systems (Java, Go, C++, Python, etc.)

Hands-on experience with distributed systems, data pipelines, queues, and large-scale storage (SQL/NoSQL)

Passionate about making AI trustworthy by building the rock-solid data foundation underneath it

You think in SLOs, error budgets, failure modes, and correctness guarantees — not just features

Prior work on enterprise connectors, search/indexing, information retrieval, or security-sensitive systems is a strong plus

Comfortable with strict consistency and permission-modeling challenges

Power user of LLMs and AI tools in your own workflow- As part of the interview process, you’ll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn’t required