Staff/Sr. Software Engineer, Search Data Infrastructure

Salesforce

Staff/Sr. Software Engineer developing search data infrastructure for Slack's Core Infrastructure team.

Posted 7/2/2026full-timeSeattle • Texas, Washington • 🇺🇸 United StatesSenior💰 $172,500 - $313,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable, resilient offline indexing pipelines and distributed search systems, with a strong focus on AI integration and high availability. Proficient in optimizing Solr cluster infrastructure and conducting thorough code reviews to ensure quality and performance.

Highest-signal resume keywords

Distributed Data ProcessingSolr Cluster ManagementAI Integration in EngineeringHigh-Availability System DesignAdvanced Prompt Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Distributed Data TechnologiesSolrElasticsearchSparkHadoopMapReduceFunctional ProgrammingImperative ProgrammingAI Development ToolsSoftware Migration

Soft Skills

CollaborationTechnical Architecture InfluenceCode Review

Tools & Technologies

TerraformChefKubernetes

Industry Keywords

Search InfrastructureData Processing FrameworksProduction EnvironmentsSystem ContextEngineering Standards

Tech Stack

Tools & technologies

ChefElasticSearchGoHadoopJavaKubernetesMapReducePHPPythonRubySparkTerraform

About the role

Key responsibilities & impact

Design and develop scalable, resilient offline indexing pipelines that process and transform data for Slack's search infrastructure.
Partner with product engineering to conceptualize and ship new features for our large — and rapidly growing — user base.
Ensure high availability and reliability across our distributed search systems through thoughtful collaboration and rigorous engineering.
Drive significant business impact by contributing heavily to high-priority team projects.
Take long-term ownership of team features and systems, proactively improving their health and the health of surrounding services.
Deploy, configure, test, troubleshoot, maintain, and upgrade Solr clusters and environments.
Continuously optimize Solr cluster infrastructure and configuration to sustain cluster health and search performance.
Support our operations and customer-facing teams in triaging and resolving production issues efficiently.
Conduct thorough, collaborative code reviews that raise the quality bar across the team.
Champion improvements to engineering standards, tooling, and development processes.
Build and ship production-grade software using modern engineering practices, with AI as a core pillar of your development workflow — leveraging AI tools to deliver secure, optimized, and high-quality code at speed.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining a shared system context — an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (human- or AI-generated) for correctness, quality, security, and performance.

Requirements

What you’ll need

10+ years of hands-on experience with distributed data and search technologies.
Worked extensively with distributed data processing frameworks such as Spark, Hadoop, MapReduce, or EMR.
Experience with Solr, Elasticsearch, Lucene, or comparable search technologies.
Familiar with infrastructure and ops tooling such as Terraform, Chef, and Kubernetes.
Proficiency in functional or imperative programming languages — e.g., PHP, Python, Ruby, Go, C, or Java.
Track record of building high-availability, performant, and scalable systems that handle large volumes of data across multiple clusters in geographically distributed environments.
Experience planning, implementing, and executing software migrations and upgrades in production environments.
Confidence in contributing to technical architecture discussions and influencing technical decisions within your team.
Bring a genuine, demonstrated AI-first approach to engineering — using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Have experience integrating AI development tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) into day-to-day engineering workflows.
Possess advanced prompt engineering skills — writing precise, structured prompts and cultivating system context that makes AI outputs reliable, secure, and production-ready.

Benefits

Comp & perks

time off programs
medical
dental
vision
mental health support
paid parental leave
life and disability insurance
401(k)
employee stock purchasing program