Software Engineer, Data Foundations

Details

Glean is building a Work AI platform that combines enterprise search, an AI Assistant, and scalable AI agents. The Data Foundations team owns the end-to-end data ingestion and management layer powering these products across thousands of enterprise applications and billions of documents. This role focuses on the quality, freshness, security, and trustworthiness of enterprise knowledge used by Glean's Search, AI Assistant, and Agent products.

Responsibilities

• Build and scale connectors to SaaS and on-premises systems, including Google Workspace, Microsoft 365, Slack, Salesforce, Jira, ServiceNow, and GitHub.
• Handle full synchronizations, low-latency incremental updates through webhooks and APIs, rate limiting, and complex authentication flows.
• Build advanced data-source 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, including entity extraction, access-graph propagation, and redactions.
• Expand AI product capabilities through integrations that automate tasks, perform complex queries grounded in enterprise data, and enhance indexed corpora with live data.
• Own end-to-end correctness, freshness, and performance for petabyte-scale data flows.
• Solve problems involving ordering, idempotency, exactly-once processing, backpressure, and retries across distributed queues, workers, and storage.
• Preserve fine-grained access-control lists, deletions, and sensitivity constraints so AI answers remain grounded in content users are authorized to view.
• 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 support larger customers and additional data sources.

Requirements

• At least 3 years of experience building production backend or data infrastructure systems using technologies such as Java, Go, C++, or Python.
• Hands-on experience with distributed systems, data pipelines, queues, and large-scale SQL or NoSQL storage.
• Ability to think in terms of service-level objectives, error budgets, failure modes, and correctness guarantees.
• Experience with strict consistency and permission-modeling challenges.
• Prior experience with enterprise connectors, search or indexing, information retrieval, or security-sensitive systems is a strong plus.
• Passion for building reliable data foundations that make AI trustworthy.
• Comfortable using LLMs and AI tools in daily workflows.

Compensation & Benefits

• Base salary range of $180,000–$300,000 annually.
• Eligibility for variable compensation, equity, and benefits may apply to certain roles.
• Medical, vision, and dental coverage.
• Generous time-off policy and 401(k) contribution plan.
• Home-office improvement stipend.
• Annual education and wellness stipends.
• Regular company events and healthy lunches daily.
• The interview process includes a brief AI-focused exercise or discussion.

Work Arrangement

This is a hybrid role requiring four days per week in either the San Francisco or Mountain View office.