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Relevance Engineer – Enterprise Search & AI Hybrid

Cisco - 3 Locations

Posted May 21, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
Not verified checked Jun 13, 2026
Salary
$119K-$161K not verified - source not recorded; timestamp not recorded
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Schedule

Shift type
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Weekend work
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Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Relevance Engineer – Enterprise Search & AI Hybrid 3 Locations The application window is expected to close on: 04/13/2026 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received . This position is hybrid. Meet the Team Join Cisco's Enterprise Search team, responsible for powering intelligent knowledge discovery across the company. Our mission is to deliver highly relevant, scalable, and AI-enhanced search experiences that help employees and customers quickly find the information they need. We combine deep expertise in search infrastructure, ranking science, and distributed systems with modern Generative AI capabilities to transform traditional information retrieval into intelligent, context-aware discovery. We are a collaborative team of search engineers, data scientists, and AI practitioners who value experimentation, measurable impact, and technical excellence. What makes this team exciting is the opportunity to shape the future of enterprise search by integrating traditional information retrieval with cutting-edge AI and Retrieval-Augmented Generation (RAG) and agentic frameworks at scale. Your Impact Architect and optimize hybrid retrieval systems leveraging Elasticsearch, semantic embeddings, and re-ranking models to improve top-k relevance, latency, and downstream Generative AI response quality. Develop and tune relevance models using query analytics, behavioral signals, and experimentation frameworks to improve search outcomes. Integrate Generative AI capabilities with traditional information retrieval systems to create intelligent, context-aware search experiences. Implement and optimize Retrieval-Augmented Generation (RAG) pipelines that combine structured and unstructured enterprise data sources. Partner with AI engineers, platform teams, and product stakeholders to define measurable improvements in

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Apply link verified; last checked Jun 13, 2026.

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