WHO WE ARE A lot of enterprise work still happens by hand. People copy-paste between spreadsheets, live in endless email threads and click through clunky legacy UIs. We started Duvo to end that for good. Customers already trust us with business-critical processes, and our agents are automating them today. We're growing fast, and to win from here we need exceptional people. That's where you come in. We're a team of 60, with 22 engineers, and we just raised a $32 million Series A led by Balderton Capital https://www.duvo.ai/blog/duvo-raises-32-million-series-a-balderton-capital. WHAT WE ARE BUILDING Duvo is the AI operations platform for large enterprises. Right now we're focused on retail and consumer packaged goods. Customers build AI agents in Duvo that do the work wherever it lives: SAP, spreadsheets, supplier portals, email, APIs, you name it. We're heavy on browser and computer use. Business users say what outcome they want. The agents plan, act, ask for approval on exceptions and get better with every run. To help customers figure out what to automate, we also map their processes from interviews and internal docs, which gets our foot in the door. We start with the parts of a company we know best (category management, supply chain, finance ops), where we can show value fast, and expand from there to other functions and sectors. Velocity is our moat. We ship fast and iterate even faster. THE ROLE You'll lead the push to level up reliability across Duvo. Your team's mission is to earn and keep the trust of customers who run their critical business workflows on Duvo. First, AI lets developers and non-developers alike ship code much faster. We need a seasoned SRE who rolls up their sleeves and keeps Duvo reliable at that kind of velocity. Two things sit at the heart of your work: observability, and the release process, which means building canary and A/B deployment pipelines plus the tooling for fast, reliable rollbacks. You'll evolve our infrastructure topology to match. Second, at the core of Duvo, agents run complex customer workflows through reasoning and heavy tool use. You make sure we spot misbehaving agents early, understand how they fail and know what causes high latency. When bugs creep in, the tooling you built sounds the alarm before customers notice. It gives the on-call team what they need to assess impact and mitigate in minutes, not hours. And you're not afraid to add friction so post-mortem action items actually get done across engineering, on time. SREs at Duvo are intense about delivering impact fast. WHAT WE'RE LOOKING FOR These are the non-negotiables, and it's what we'll evaluate you on: - Distributed systems. You've designed and run systems that scale. You understand failure modes, capacity planning and the tradeoffs between consistency, availability and latency in real production environments. - Security mindset. You'll handle enterprise data flowing through sandboxed environments, manage KMS encryption, configure Cloud Armor WAF rules and keep tenant workloads isolated on the network. Security is a default for you, never an afterthought. - Observability and incident response. You have strong experience with observability tooling (no specific tool required) and you've built monitoring and alerting in production. When an incident hits, you lead a structured response, find the root cause and drive a lasting fix, beyond a restart. - Infrastructure as code and automation. You automate everything you can. You've run IaC tools, CI/CD pipelines and container orchestration in production. - Shipping and ownership. You improve systems instead of just maintaining them. You own reliability projects from proposal to production, and you measure the results. - Judgment on where to invest. You decide what to automate first and where to invest in reliability versus shipping speed, and you make incident calls with incomplete information. YOU MIGHT ALSO - Have experience with GCP, Kubernetes or similar cloud-native infrastructure. - Have worked with sandboxed execution environments or multi-tenant isolation. - Know the reliability challenges that are specific to LLM-based applications in production. - Have a product engineering background. You've built features and you understand the developer experience you're supporting. THIS IS NOT FOR YOU IF - You want a traditional ops role where you follow runbooks. We're building the reliability practice, not maintaining one. - You mostly want to build AI features. Check out our AI Platform Engineer role instead. LOCATION We're looking for people based in Europe, in European time zones, so we overlap for most of the working day. OUR TECH STACK - GCP (Cloud Run, GKE, GCS) - Terraform, Docker - Datadog - TypeScript and Python services (you'll read and occasionally modify application code, but deep language expertise isn't required) - Postgres, Redis HOW WE WORK These are real tradeoffs we made: - Initiative-driven. We organize around customer problems instead of org charts. Problems come from product feedback, competitive analysis and talking to customers directly. Then we prioritize, build and ship every week. - Customer-obsessed. We work on real problems for real customers, not hypothetical ones. - Iterative by default. We ship small, learn fast and don't get attached to yesterday's code. Things break sometimes, and we fix forward. - AI first. We use AI to go faster and spend human time where it really matters. If a tool can do it, a person shouldn't. - Direct feedback. We tell each other right away what to improve. It can feel uncomfortable, and we think it's worth it. - Autonomy with accountability. We trust people to make the call, and we judge them on outcomes. WHAT WE OFFER - A competitive salary and a generous ESOP allocation in a fast-growing company, fresh off our Series A. - Unlimited spend (within reason) on the AI tooling of your choice. - If you're remote, we reimburse your co-working space if that's where you feel most comfortable. - Travel: frequent visits to our Prague office, offsites (our upcoming engineering retreat includes a day at the Porsche Experience Center Hockenheimring) and conferences (we recently sponsored Lisbon AI). - Autonomy to do your best work. Want to meet someone to learn from? Set it up. Want a mentor? Go get one. - A real AI product used by enterprise customers. No demos, no internal tools. - Many AI modalities in one product: voice agents, computer and browser use, reasoning, and long-running agents. Applied AI, not research. - A sharp, motivated team that values ownership and candor. HOW WE HIRE We respect your time and move fast: 1. Application review. We read your application against what's listed under "What we're looking for". 2. Screening call (30 min). A short call with our recruiter to check your experience against your CV and make sure the basics fit. 3. Discovery interview (30 min). A conversation with our hiring manager about your background, how you think and how you communicate. 4. Technical interview (60 min). A deep dive into your technical skills and how they fit the team's needs, with engineers from our team. 5. Trial day (1 day). You get an ambitious problem in the morning, work on it with the team, have a check-in with one of our founders, and present what you built at the end of the day. 6. Offer. If the trial day goes well, we move quickly to an offer.