Senior Staff Software Engineer- Search Quality

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Senior Staff Software Engineer- Search Quality Bengaluru, India P-1408 The Mission We are democratizing Data and AI for every enterprise user. Our vision is a world where anyone can master their organization's data through Apps and AI Agents. We are building the retrieval backbone for two worlds: the high-precision context layer for AI agents and the intuitive search experience for people goal is the same: instant, accurate, and actionable insight. The Role : - As a Search Quality Engineer, you sit at the heart of this transformation. You aren't just building a search engine; you are building the contextual backbone of the entire company. - You will own the quality of results for two distinct but deeply connected "users": - The AI Agent: Optimizing the retrieval layer that allows LLMs to reason over data they weren't trained on, ensuring they have the "ground truth" needed to synthesize accurate, high-stakes business actions. - The Human User: Improving the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces. The Technical Challenge This isn't a solved problem. You will be tackling "Search" in its most evolved form: - Hybrid Retrieval: Balancing traditional keyword-based search (for exactness) with semantic vector search (for intent). - Dual-Optimization: Fine-tuning ranking models that satisfy both human readability and LLM-ready context. - High-Stakes Accuracy: In a world of Agents, poor search quality leads to hallucinations. You will build the guardrails and relevance scoring that ensure our AI stays grounded in reality. - Data Heterogeneity:

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