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Slack is seeking experienced engineers to join its Core Infrastructure organization — the team responsible for designing, developing, and maintaining the information retrieval systems that power Slack Search and a broad range of product experiences.

This infrastructure sits at the heart of what makes Slack an indispensable repository of company knowledge, enabling millions of users to instantly surface messages, channels, people, files, and business-critical information across their workspaces. It's also foundational to our generative AI initiatives — helping build intelligent products grounded in the full depth of your organization's knowledge.
We're looking for engineers who are passionate about pushing the boundaries of search technology, driving our systems toward greater reliability, performance, scalability, and security — and who are excited to bring the latest advances in information retrieval to a platform used by the world's best teams.

Our stack is built on proven, trusted tools including Java, Go, PHP/Hack, Python, MySQL, Solr, Kubernetes, Terraform, AWS, and Linux. Deep expertise in these technologies is a strong plus, but what matters most is a track record of building and operating robust distributed systems for search — regardless of the specific language or cloud platform. We're a genuinely collaborative team that values curiosity, craft, and working closely with infrastructure engineers, ML engineers, product engineers, and product managers to deliver exceptional search experiences at scale.

Slack has a positive, diverse, and supportive culture — we look for people who are curious, inventive, and committed to being a little better every single day. In our work together, we aim to be smart, humble, hardworking, and above all, collaborative.

• 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.

What you should have:

• 10+ years of hands-on experience with distributed data and search technologies.

• Have worked extensively with distributed data processing frameworks such as Spark, Hadoop, MapReduce, or EMR.

• Experience with Solr, Elasticsearch, Lucene, or comparable search technologies.

• Are 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.

• You've built large-scale data pipelines in a professional setting and can craft clean, elegant code in Java, Scala, and/or SQL, with solid exposure to Hadoop and/or Spark.

• You have experience in text mining, parsing, and NLP techniques applied to search relevance or data enrichment.

• You've contributed to or led efforts around search relevance tuning, ranking models, or query understanding.