Software Engineer

About Readyset

At Readyset, we are building a database cache with zero integration cost - just swap your connection string and take read latencies from ~100's of ms to under a ms while reducing costs. It precomputes the results of prepared statements (i.e. parameterized SQL queries) and incrementally updates these results over time as the underlying data in your database changes.

Readyset is wire-compatible with MySQL and Postgres, so it can be integrated with your existing application without code or database changes– Readyset makes it easy for developers to build performant web, analytical, and internal applications regardless of whether they’re deployed to a single region or around the world. 

We’re looking for people who are excited about exploring and productionizing the frontier of distributed systems and DB research to join our fully-remote team. You’d be a great fit at Readyset if you're excited about bringing to market data infrastructure that makes applications faster, simpler, and easier to deploy.

About this role

We’re looking for a Staff Software Engineer to help build the next generation of AI-native cloud infrastructure: systems that power data-intensive products and bring advanced AI capabilities into production. Our Cloud and AI team moves fast and delivers what others call impossible, shipping ambitious systems at breakneck speed while maintaining engineering rigor.

The challenges we’re tackling are the ones that define enterprise-scale AI systems:

• Freshness: ensuring data is always current, since stale results immediately erode user trust.
• Memory: designing structured, retrievable memory so agents can behave reliably over time, not just like short-lived chatbots.
• Cost: keeping re-embedding, reranker passes, and LLM calls sustainable through batching, caching, and smart model routing.

We believe solving these challenges is key to making AI systems production-grade: responsive, reliable, and affordable at scale. As a Staff Engineer, you’ll play a central role in designing and operating the infrastructure that makes this possible.

Responsibilities 

• Design and own critical services**:** hands-on development of systems that are robust, scalable, and simple to operate in production.
• Lead high-impact architectural decisions, balancing speed with sound engineering for 3–4 9s availability.
• Work across the stack, from distributed cloud infrastructure to AI-driven features like retrieval, memory, and agent orchestration.
• Collaborate with leadership and product teams to translate ambitious ideas into reality, fast.