Company Name: ReadySet

Job Details: $190-240k+,EquityAWSGCPPythonJavaAzureGolangRustExpert,levelRemote,from,US

Job Url: https://app.welcometothejungle.com/jobs/PooS1lc3?theme=female-leaders

Job Description: RoleWho you areWe’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 deploy10+ years of software engineering experience, ideally with exposure to databases, data platforms, or large-scale systemsProven ability to design and run cloud services at scale with high availability (3–4 9s)Experience with AI/ML systems or integrating LLMs into production (retrieval pipelines, memory systems, agent frameworks)Expert backend development experience in Python, Golang, Java, Rust etc.; familiarity with modern frontend frameworks a plusDeep familiarity with AWS (experience with GCP/Azure a plus)Demonstrated technical leadership: shaping architecture, influencing design, and guiding teams through complexityA mindset for velocity with rigor: moving fast without compromising sound engineeringWhat the job involvesWe’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 productionOur Cloud and AI team moves fast and delivers what others call impossible, shipping ambitious systems at breakneck speed while maintaining engineering rigorThe 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 trustMemory: designing structured, retrievable memory so agents can behave reliably over time, not just like short-lived chatbotsCost: keeping re-embedding, reranker passes, and LLM calls sustainable through batching, caching, and smart model routingWe 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 possibleDesign and own critical services: hands-on development of systems that are robust, scalable, and simple to operate in productionLead high-impact architectural decisions, balancing speed with sound engineering for 3–4 9s availabilityWork across the stack, from distributed cloud infrastructure to AI-driven features like retrieval, memory, and agent orchestrationCollaborate with leadership and product teams to translate ambitious ideas into reality, fastAct as a technical leader: mentor engineers, drive engineering culture, and shape the way we build as we scaleContribute to Readyset’s engineering strategy and vision, not just individual projectsShare this jobReport a problem with this jobHide companyCompanyFunding (1 round)Apr 2022$29mSERIES ATotal funding: $29mOur takeOnce applications begin to gain popularity, databases need to be able to handle an increased volume of requests, larger data sets, and more complicated queries. Databases that can’t keep up can lead to substantial business losses precisely when there’s most to be gained: Super Bowl weekend, for example, or Black Friday. ReadySet is looking to help companies dodge this issue.The company has developed a plug-and-play data caching layer that pre-computes and caches query results in relational databases, meaning that database reads can remain fast. In fact, ReadySet claims that the layer supports millions of reads per second “with sub-millisecond latencies on a single node”.This is a hugely impressive feat from the company, founded by a team of data systems researchers from MIT, for whom ReadySet began as Noria - the open source streaming data-flow system developed in the lab. Plus, surveys suggest that there’s substantial enterprise appetite for this kind of product. This is partly thanks to unfit legacy systems, and partly in anticipation of the swelling user and data volumes anticipated for the years ahead - both are good news for ReadySet.FreddieCompany Specialist at Welcome to the Jungle