Description
About the Team
Slack is the place where work happens — and Search is at the heart of it. We're looking for experienced engineers to join our Core Infrastructure organization, where you'll help design, develop, and maintain the information retrieval systems that power Slack Search and a wide range of product experiences.
Our search stack is central to what makes Slack an indispensable store of organizational knowledge — enabling millions of users to instantly find messages, channels, people, files, and business-critical information across their workspaces. It's also foundational to our generative AI efforts, helping build intelligent products that leverage the full breadth of your company's knowledge graph.
If you're excited about pushing the boundaries of information retrieval, building systems that scale to meet the demands of the world's most collaborative teams, and doing it all in an environment where your work directly shapes the product — this is the role for you.
We build our infrastructure on reliable, battle-tested tools our team knows and trusts: Java, Go, PHP/Hack, Python, MySQL, Solr, Kubernetes, Terraform, AWS, and Linux. Expertise in these is a strong plus — but solid experience building and operating robust distributed search systems using other languages and cloud technologies is a great substitute.
We're a tight-knit, collaborative team who genuinely enjoy working together. You'll partner closely with infrastructure and machine learning engineers to evolve our systems, and collaborate with product engineers and managers to ensure our infrastructure meets the needs of our users.
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.
What you will be doing:
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 growing!) user base.
Collaborate with team members to ensure high availability and reliability of a distributed search system at massive scale.
Own team features and systems end-to-end, defining their long-term health while proactively improving the health of surrounding systems.
Deploy, configure, test, troubleshoot, maintain, and upgrade Solr clusters and environments.
Continuously optimize the infrastructure and configuration of our Solr clusters to maintain cluster health and peak search performance.
Support our skilled operations team in triaging and resolving production issues quickly and effectively.
Raise the bar on engineering standards, tooling, and processes across the team.
Build and ship high-quality, production-grade software using modern engineering practices — with AI as a core part of your development workflow.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining 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.
You may be a fit for this role if you:
Have 4+ years of applicable software engineering experience.
Have worked extensively with distributed data processing frameworks such as Spark, Hadoop, MapReduce, or EMR.
Have hands-on experience with Solr, Elasticsearch, Lucene, or other search technologies.
Are familiar with infrastructure/ops tools and frameworks such as Terraform, Chef, and Kubernetes.
Are proficient with functional or imperative programming languages — e.g., PHP, Python, Ruby, Go, C, or Java.
Have a track record of building high-availability, performant, and scalable systems that handle large data volumes across multiple clusters and geographic regions.
Have experience planning, implementing, and deploying software migrations and upgrades in production environments.
Can contribute meaningfully to technical architecture discussions and help drive sound technical decisions within your team.
Are a strong communicator — able to explain complex technical concepts clearly to designers, support staff, and fellow engineers.
Possess solid computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.
Bring a genuine, demonstrated AI-first approach to engineering — using AI tools to move faster, build fluency across the stack, and contribute beyond your core specialty.
Have experience integrating AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) into your development workflow.
Have advanced prompt engineering skills — able to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
Bonus Points:
You've built large-scale data pipelines professionally and can write clean, elegant code in Java, Scala, and/or SQL, with hands-on exposure to Hadoop/Spark.
You have experience with text mining, NLP, or natural language parsing.
You've contributed to relevance tuning, ranking systems, or query understanding.
You have familiarity with vector search, dense retrieval, or embedding-based approaches to information retrieval.