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Glean

AI-powered enterprise search across applications

AI Data Analyst

Manual & Functional QAConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • 3–5 years of experience in data labeling, data analysis, quality assurance, or a related field.
  • Strong analytical judgment and attention to detail, with the ability to apply nuanced rubrics consistently.
  • Experience evaluating AI-generated outputs or working with natural language processing, search, recommendation, or other machine learning systems.
  • Familiarity with structured qualitative analysis, basic SQL and data retrieval, and spreadsheet-based workflows.
  • Clear written and verbal communication skills, with the ability to explain findings to technical and non-technical audiences.
  • Ability to work independently in ambiguous, fast-moving environments and collaborate effectively across functions.

Responsibilities

  • Run ongoing human labeling for priority AI workflows, including response quality, task success, Model Context Protocol and tool use, and end-to-end Cowork-style workflows.
  • Triage bad-query reports, downvotes, escalations, and routed quality issues; categorize failure modes and feed clean analysis back to partner teams.
  • Perform qualitative analysis to identify recurring patterns such as hallucinations, retrieval failures, tool-use issues, weak grounding, and poor workflow completion.
  • Follow and improve labeling guidelines and rubrics so judgments are consistent, realistic, and useful for model and product improvement.
  • Maintain high-quality labeled datasets, golden sets, and regression slices; monitor coverage, drift, leakage, and difficulty distribution.
  • Participate in calibration exercises with human graders and validate large language model-as-a-judge outputs against human labels to improve consistency and judge quality.
  • Partner with engineers, product managers, quality assurance, and evaluation owners on pre- and post-change quality reads, benchmark updates, and release-readiness decisions.
  • Contribute to recurring quality reporting by surfacing top failure modes, coverage gaps, quality shifts, and actionable recommendations.

About the Company

Glean

AI-powered enterprise search across applications

Glean builds an AI-powered search and knowledge assistant that helps employees find information across all of a company's apps and data. Its core product is an enterprise search tool that understands natural language queries and retrieves relevant results from documents, conversations, tickets, and other sources, plus a chat assistant that can summarize and answer questions using that same information. The system uses deep learning language models that adapt to a company's own terminology and context, improving relevance without manual tuning, and it offers hosting options to align with security and data policies. Compared with competitors, Glean focuses on cross-application search, organization-specific language learning, and a combined search-and-chat experience that delivers direct answers and summaries from internal knowledge sources. Its goal is to help teams work faster by turning scattered information into easily accessible answers, reducing time spent searching.

Company size
1,001-5,000
Company stage
Series F
Total funding
$805M
Headquarters
Palo Alto, CA
Founded
2019

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