Software Engineer, Data Foundations
Glean
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Skills named in this job
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This role on the market
180 open foundations roles across 53 companies are on ApplySarthi right now, most of them in Bengaluru (2).
- Full-stack Engineer 4 - Intelligent Foundations and Experiences (IFX)Capitalone
- RE/RS, Data Understanding - FoundationsOpenAI
- Senior iOS Engineer, Media Foundations - BeRealBeReal
- Senior Research Scientist, AI Foundations RecipesWaymo
- Sr Product Manager - Technical, Rendering FoundationsAmazon.com Services LLC
What foundations roles keep asking for: Python (14%), System design (13%), AWS (13%) — counted across their open postings here.
Software Engineer jobs in the United States · Software Engineer jobs in San Francisco · Remote Software Engineer jobs · C++ jobs · Go jobs · Java jobs · LLMs jobs
Glean has 130 open roles listed here.
- Machine Learning Engineer, Search Quality
- Designated Technical Support Engineer - Central/East
- Strategic Federal Account Executive, SLED
- Designated Technical Support Engineer - Central/East
- Principal Product Marketing Manager (Enterprise Context)
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for foundations roles keep coming back to Python, System design, AWS. Practise those questions before you sit with Glean.
Questions you are likely to be asked
- Why do you want to join Glean?
- What is your experience with LLMs? Tell me one thing you learned the hard way.
- Walk me through a system you built. How was it designed, and what would you change now?
- Tell me about a hard bug you tracked down. How did you find the cause?
- How do you decide what to test, and what does good code review look like to you?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Software Engineer, Data Foundations at Glean interview free →- 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 either our San Francisco or Mountain View office)
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Listed on greenhouse · posted 2025-12-08. ApplySarthi collects openings and links to application pages; the role is advertised by Glean, not by us.