Hiring.Camp

Principal Search Engineer for Elasticsearch/OpenSearch in Content Ecosystems

Hyland

ยท

2 days ago

Location
Hyderabad, TG, IN
Workplace
Hybrid
Type
Full-time
Department
Engineering
Seniority
Lead
Closing date
Today
Source
iCIMS

Description

Overview

Principal Search Engineer โ€“ Elasticsearch

๐Ÿ“ Location: Hyderabad ๐Ÿข Work Arrangement: Hybrid โ€“ 2 days per week in the office

About the Role

We're looking for a seasoned and technically exceptional Principal Search Engineer to join our team and take ownership of Hyland's search infrastructure at scale. In this role, you'll bring deep, production-proven expertise in Elasticsearch and OpenSearch to architect, scale, and operate search systems that power real workloads โ€” not just dev environments.

This is a high-impact, highly technical role for an engineer who thinks in systems, operates with an ownership mindset, and is energized by the challenge of building search infrastructure that is fast, reliable, and built to last. If you've spent years working at the intersection of full-text search and vector search, and you understand what it takes to run these systems under real production constraints, we'd love to connect.

Your Role Responsibilities? Here's What You'll Do.

  • Design, build, and operate large-scale Elasticsearch and OpenSearch clusters in production โ€” including cluster sizing, shard strategy, and multi-tenancy architecture to support evolving data models and real production constraints.
  • Lead search infrastructure design and systems architecture, ensuring search workloads are optimized for scale, resilience, and long-term performance across Hyland's product portfolio.
  • Drive performance tuning, capacity planning, and incident response readiness across search infrastructure โ€” establishing monitoring disciplines and observability practices to proactively identify and resolve issues before they impact customers.
  • Architect and implement k-NN vector indexing, embedding storage, and quantization strategies, integrating vector search capabilities seamlessly alongside traditional full-text search workloads.
  • Collaborate with cross-functional engineering teams to integrate search across multiple products and repositories, ensuring consistency, quality, and a shared search layer that serves diverse content systems.
  • Establish and evolve search engineering standards, contribute to technical roadmaps, and mentor engineers on search infrastructure best practices, relevance tuning, and operational excellence.

Technology Tools

  • Elasticsearch
  • OpenSearch
  • k-NN Vector Indexing
  • AWS OpenSearch Service
  • Elastic Cloud

Role Essentials

  • 15+ years of software engineering experience, with significant depth in search infrastructure and a strong track record of production success.
  • Deep production expertise with Elasticsearch or OpenSearch โ€” you've built, scaled, and operated clusters under real production constraints, not just used them in dev environments.
  • Strong systems design skills โ€” ability to architect search workloads for scale, multi-tenancy, and evolving data models across complex enterprise environments.
  • Operational mindset โ€” proven experience with performance tuning, capacity planning, incident response readiness, and monitoring discipline in high-availability environments.
  • Experience with k-NN vector indexing, embedding storage, and quantization strategies โ€” with a deep understanding of how to integrate vector search alongside traditional full-text search.

What We'd Like to See

  • Experience integrating search across multiple products or repositories, especially in environments where different content systems share a common search layer.
  • Familiarity with content and document domain concepts โ€” including metadata modeling, ACL-aware search, large binary handling, and document lifecycle management.
  • Familiarity with AWS OpenSearch Service or Elastic Cloud in production, including cost optimization strategies and cluster sizing best practices.
  • Experience with search observability โ€” building dashboards, conducting slow-query analysis, and developing relevance measurement frameworks.
  • Background in multi-cloud or hybrid deployment models for search infrastructure at enterprise scale.

About Hyland

Hyland is the pioneer of the Content Innovation Cloudโ„ข, delivering ubiquitous enterprise intelligence to organizations with solutions that unlock actionable insights and drive automation.

Trusted by thousands of organizations worldwide, including many of the Fortune 100, Hyland's solutions create the foundation for a connected, agentic enterprise, where teams harness the power of AI to redefine how they operate and engage with those they serve. For additional information on Hyland's platform and services, please visit Hyland.com.

ยฉ Hyland. All rights reserved.

About Hyland Life

#HylandLife

Since 1991, it has been Hyland's mission to help our employees, customers and partners exceed their potential with our industry-leading content services platform. Our employees exude a contagious energy and are passionate about what they do โ€“ whether it's helping customers succeed, raising up their fellow Hylanders, or engaging in the communities where they live and work.

The #HylandLife hashtag encompasses our employee-centric culture. Our employees live our culture day in and day out by bringing their best self to work. Hyland supports them to do just that through career development resources, wellbeing programs and innovation practices. We thrive on diverse viewpoints and new ideas and believe that a positive, inclusive workplace is imperative to sustainable success.

As we've grown to a company of nearly 4,000 strong, we have the opportunity to make a significant impact on our communities. We strongly support employee initiatives and align our giving campaigns and programs to organizations that are important to them.

Equal Opportunity Statement

Hyland is an equal opportunity employer. We value diversity and are committed to providing an inclusive workplace for all employees and applicants. Employment decisions are made without regard to any characteristic protected by applicable laws and regulations. Information collected during the hiring process is used solely to assess qualifications, verify identity, and comply with legal requirements.

ย 

Skills

AWSElasticsearch

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