Staff/Senior Software Engineer (Search Data Infrastructure)

TL;DR

Staff/Senior Software Engineer (Search Data Infrastructure): Designing and developing scalable, resilient offline indexing pipelines for Slack's search infrastructure with an accent on distributed systems, search technology, and high-availability architecture. Focus on building intelligent products grounded in organizational knowledge, integrating AI agents into workflows, and optimizing Solr clusters for performance at scale.

Location: Must be based in Seattle, Atlanta, or Dallas

hirify.global

A global leader in cloud-based software and CRM solutions, powering the Slack platform to connect teams and information.

What you will do

• Design and develop scalable, resilient offline indexing pipelines for search infrastructure.
• Partner with product engineering to conceptualize and ship new features for a large user base.
• Ensure high availability and reliability across distributed search systems.
• Deploy, configure, and optimize Solr clusters and environments.
• Build production-grade software using modern engineering practices with AI as a core pillar.
• Design and orchestrate complex systems where AI agents integrate into human workflows.

Requirements

• 10+ years of hands-on experience with distributed data and search technologies.
• Experience with distributed data processing frameworks like Spark, Hadoop, or EMR.
• Proficiency with Solr, Elasticsearch, or Lucene.
• Familiarity with infrastructure tooling such as Terraform, Chef, and Kubernetes.
• Demonstrated AI-first approach to engineering with experience using AI development tools.
• Advanced prompt engineering skills and ability to cultivate system context for AI reliability.

Nice to have

• Experience in text mining, parsing, and NLP techniques.
• Contributions to search relevance tuning, ranking models, or query understanding.
• Professional experience building large-scale data pipelines in Java, Scala, or SQL.

Culture & Benefits

• Collaborative and supportive team environment valuing curiosity and craft.
• Commitment to diversity and inclusive engineering practices.
• Focus on continuous improvement and high-quality engineering standards.
• Opportunity to work on foundational infrastructure for generative AI initiatives.