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. You'll be 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 confidence. About you: 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). You think in SLOs, error budgets, failure modes, and correctness guarantees — not just features. 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. Passionate about making AI trustworthy by building the rock-solid data foundation underneath it. Power user of LLMs and AI tools in your own workflow. Location: This role is hybrid (4 days a week in our Mountain View office) Compensation & Benefits: The standard base salary range for this position is $180,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. 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. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.

Requirements

Must-haves

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 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).
You think in SLOs, error budgets, failure modes, and correctness guarantees — not just features.
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.
Passionate about making AI trustworthy by building the rock-solid data foundation underneath it.
Power user of LLMs and AI tools in your own workflow.
This role is hybrid (4 days a week in our Mountain View office)
Global Data Privacy Notice for Job Candidates and Applicants:
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.

Nice-to-haves

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Application prep

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Keywords to mirror

aillmjirajavagopythonsql

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Wellness