Software Engineer, Data Foundations

Gleanwork; San Francisco (CA); Hybrid; USD 140,000 - 265,000; Full time

Benefits offered by this job

Medical, vision, and dental coverage

Generous time-off policy

401(k) plan contributions

Home office improvement stipend

Annual education and wellness stipends

Job summary

Gleanwork is looking for a Software Engineer to enhance Glean's data management layer, essential for their AI Assistant and Search products. The role involves building connectors and transforming enterprise content into structured formats.

Ideal candidates will have over 3 years of experience in data infrastructure and be familiar with distributed systems. This hybrid role requires work in both San Francisco and Mountain View offices. We offer a competitive salary and comprehensive benefits.

Qualifications

• 3+ years building production backend or data infrastructure systems (Java, Go, C++, Python).
• Hands-on experience with distributed systems, data pipelines, queues, and large-scale storage.
• Experience in developing enterprise connectors or security-sensitive systems is a strong plus.

Responsibilities

• Build and scale connectors to various SaaS and on-prem systems.
• Handle full syncs, low-latency incremental updates via webhooks/APIs.
• Transform raw enterprise content into structured representations optimized for search.

Skills

Production backend or data infrastructure systems

Distributed systems experience

Data pipelines and queues

Large-scale storage (SQL/NoSQL)

Understanding of error budgets and SLOs

Enterprise connectors experience

Job description

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.

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, 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.

Qualifications

• 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 either our San Francisco or Mountain View office).

Compensation & Benefits

The standard base salary range for this position is $140,000 - $265,000 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 401(k) plan. When you join, you’ll receive a home office improvement stipend and annual education and wellness stipends.

Equal Opportunity

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 are 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.