Senior Index Team Engineer
About Kagi
Kagi is your companion for a better web. We're building a friendly internet where you can explore, learn, and interact with confidence - free from ads, tracking, and distractions. Kagi builds advanced, user-centric technology to empower you, not replace you.
Our products include Kagi Search, Orion browser, Kagi Assistant, Kagi News, Kagi Summarizer, and Kagi Translate. Every product reflects our commitment to a surveillance-free internet, designed around the user.
About the Index Team
The Index team builds and maintains Kagi's own search index - the layer that makes our results meaningfully different from everyone else's. While most search engines stop at aggregating results from the same sources, we go further: we build, maintain, and continuously improve our own index to give Kagi users results that nobody else can offer. It's a hard technical problem involving distributed job scheduling, large-scale data pipelines, index quality engineering, and real-time monitoring - and the work directly shapes what millions of searches return.
The Role
What You'll Do
• Embed within the Search team to ensure index improvements translate into better results for user.
• Design and improve the URL frontier and crawl job scheduling system - how we decide what to index, when, and in what order
• Own and evolve the indexing strategy (what we index post-crawl) and ranking implementation.
• Investigate and fix index quality issues - spam, stale content, deduplication, coverage gaps
Must-Haves
• 5+ years of backend engineering experience in production information retrieval/search systems
• Prior experience with search index infrastructure, URL frontier systems, or crawl scheduling
• Deep expertise across the information retrieval stack: index design, relevance scoring and ranking optimization, near-duplicate detection, query engine architectures, and graph-based signal extraction.
• Strong database skills - you're comfortable designing and optimizing complex PostgreSQL schemas and queries, including large job/task tables that need to scale
• Proficiency in Python and/or Rust - our primary languages for this work
• Ability to reason about large-scale data pipelines: throughput, correctness, idempotency, and operational reliability
• Experience with observability tooling (Prometheus, Grafana or similar)
• Comfort with Redis for distributed state and queue management
• Experience with distributed job scheduling or work queue systems - you understand the failure modes and edge cases
• Experience operating systems where correctness and data quality are the primary constraints
If you've ever spent a week tracking down a subtle bug in a distributed job scheduler and felt proud rather than defeated at the end of it, this is the role.
Originally posted on Himalayas