Staff Software Engineer, Search Data Infrastructure - Slack

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Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

*IN SCHOOL OR GRADUATED WITHIN THE LAST 12 MONTHS? PLEASE VISIT FUTURE FORCE FOR OPPORTUNITIES*

About the Team

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.

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 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)