Staff Backend Engineer, AI Platform

ppZurich, Switzerland | Full-time | Primarily in office | Working language: English | Visa sponsorship is not available /p pbBuild the systems that let engineering teams measure and improve their coding agents. You'll turn methods developed through research and customer deployments into repeatable evaluations, reliable monitoring, and reusable product capabilities. /b /p h3About LogicStar /h3 pbWe make software engineering agents measurably better. /b /p pLogicStar helps engineering teams determine where coding agents work reliably, where they fail, and where human supervision can be safely removed. Starting with pull-request review, we use customers' repositories and engineering history to build repeatable evaluations and monitor performance as agents change. /p pLogicStar was founded in Zurich by members of the team behind DeepCode, which was acquired by Snyk. Today, we are a 12-person team backed by Northzone and Bek Ventures. /p pWe combine production engineering with research in machine learning for code, software verification, and agent evaluation. /p h3The role /h3 pWe're looking for a strong backend engineer with experience building and operating reliable production systems. Experience with coding agents, LLM applications, evaluations, or benchmarks is a plus. /p pYou'll report directly to our CTO and work closely with our architect in a hands-on Staff engineering role, turning research methods and customer implementations into reliable production systems. You'll take technical ownership of important parts of LogicStar's evaluation and monitoring platform, making architecture and implementation decisions within your areas of responsibility and helping shape engineering direction across the platform. /p pWorking from our Zurich office and occasionally at customer sites, you'll own ambiguous problems from start to finish: break them into tractable work, make sound technical trade-offs, and write critical code. Through mentoring and collaboration, you'll help other engineers deliver independently and raise the engineering standard around you. /p h3What you will do /h3 ul libTurn research into reusable product capabilities. /b Develop methods validated in experiments and early customer projects into tested, maintainable platform capabilities behind clear abstractions, APIs, and configuration. /li libOwn and evolve core platform components. /b Take responsibility for important parts of our evaluation and monitoring platform, building on work already underway. Depending on your strengths and our priorities, this could include deriving reference outcomes from repository history, constructing reproducible benchmarks, enabling historical replay and agent scoring, or monitoring agents in production. /li libSet a high engineering bar. /b Build systems that are reliable, secure, observable, and straightforward to operate. Use AI coding agents effectively in your own work and help the team establish best practices around their usage. Write critical code and review the work of others. /li libMentor less experienced engineers. /b Help them improve technical judgment, break down work, and deliver with greater independence. /li libWork directly with customers. /b Understand their engineering systems and constraints, build solutions for their specific needs, and explain technical choices clearly. Use what you learn to guide product decisions and identify which customer-specific capabilities should become part of the shared platform. /li /ul h3Minimum Qualifications /h3 ul liTypically 8+ years of professional software engineering experience, with a record of shipping and operating production systems. /li liThe ability to work across backend services, data pipelines, and cloud infrastructure. /li liStrong Python skills and experience with at least one of Go, TypeScript, or C++. /li liExperience designing systems and APIs that remain understandable as the product, team, and customer base grow. /li liEvidence that you can turn prototypes, research ideas, or uncertain technical approaches into dependable software. /li liA track record of mentoring engineers through design discussions, code reviews, and day-to-day delivery. /li liComfort working directly with customers and translating their problems into technical requirements. /li /ul h3Helpful Experience (roughly in priority order) /h3 ul liBuilt SaaS products that can also run in customer cloud accounts or on-premises. /li liBuilt or operated evaluation pipelines and used their results to diagnose failures, compare approaches, or make release decisions. /li liBuilt and debugged LLM-based agents. /li liBuilt observability systems for LLM applications, including trace collection and analysis. /li liWork on an urgent new problem: how companies measure, release, and trust software engineering agents as part of software factories. /li liJoin a small, highly technical team with experience building and scaling AI systems for software engineering. /li liMeaningful influence and ownership over the architecture, engineering culture, and product direction. /li liCompetitive salary and a meaningful equity grant reflecting the scope, seniority, and long-term impact of the role. We discuss compensation expectations early in the process. /li liIn-person culture with an office in central Zurich. /li li25 days of holiday on top of public holidays. /li /ul pLogicStar AG is an equal opportunity employer. We value different backgrounds and are committed to an inclusive working environment. /p /p #J-18808-Ljbffr