Senior Software Engineer, Algolia

• Experience designing and operating production pipelines (batch, streaming, or hybrid) and being accountable for their reliability
• Confidence working with large datasets and high-traffic systems, and a pragmatic approach to performance, scaling, and cost
• Experience building and maintaining API services used by internal teams and/or external customers
• Strong engineering fundamentals: high code quality, automated testing, and maintainable design in evolving codebases
• Experience with a major cloud provider (GCP, AWS, or Azure), plus comfort debugging production issues using logs, metrics, and traces
• Excellent spoken and written English

Desirable

• The Relevance Group is dedicated to advancing the core search experience by improving both pre-query relevance (Understanding) and post-query relevance (Ranking)
• Within the Ranking team, we own key customer-facing capabilities like AI Re-Ranking, helping customers get better results with measurable impact. We’re looking for problem solvers with an entrepreneurial mindset, people who focus on outcomes and use data to drive decisions
• The team is composed of engineers with different skill sets and backgrounds. Your experience, your knowledge, and your perspective will add to this diversity and help us deliver products that make a difference
• As a Senior Software Engineer (Ranking), you’ll be a core contributor to how Algolia ranks results at scale. You’ll work at the intersection of backend engineering, data pipelines, and applied AI, shipping features that directly improve the search experience for thousands of customers
• Design and build Ranking features end to end, from technical design through production rollout and iteration, with a clear focus on customer impact
• Build and operate production-grade pipelines that power relevance features (including AI Re-Ranking), with strong attention to correctness, reliability, and cost
• Own quality and soundness of our data flows, raising the bar on testing, observability, and operational readiness so systems behave predictably at high load
• Work closely across disciplines, collaborating with frontend engineers, ML specialists, and product partners to turn ideas into robust, customer-facing capabilities
• Use data to guide decisions, define success metrics, dig into datasets, and run experiments that make relevance improvements measurable and repeatable
• Mentor and uplift the team, through thoughtful reviews, sharing best practices, and helping build a culture of strong ownership and continuous improvement