At a Glance
- Tasks: Own the reliability and security of our AI operations platform for enterprise customers.
- Company: Join a fast-moving team on a mission to revolutionise enterprise data management.
- Benefits: Competitive salary, equity options, unlimited AI budget, and remote work flexibility.
- Other info: Be part of a motivated team with excellent career growth opportunities.
- Why this job: Make a real impact by building reliable systems that power innovative AI solutions.
- Qualifications: Experience in distributed systems, security, observability, and infrastructure automation.
The predicted salary is between 110000 - 220000 £ per year.
Who We Are
Enterprise teams still copy data between systems all day. Work gets stuck in emails, legacy UIs, and handoffs. That chaos is costly, slow, and risky. We're a fast-moving team on a mission to end it for good. Traction is strong and we're solving real problems for real customers—but to win, we need exceptional talent. We stay humble, do the work, and let results speak.
What We Are Building
We're building the AI operations platform for retail and CPG enterprises—a horizontal platform where AI agents execute end-to-end work across UIs and APIs with governance built in. Where copilots stop, Duvo finishes the job. Business users specify the outcome; agents plan, act, request approvals on exceptions, and learn with every run. We start with a retail wedge (category management, supply chain, finance ops) where ROI is obvious, then expand to adjacent functions and sectors. Velocity is our moat: ship fast, iterate faster, compound learning.
The role
You will own the reliability, security, and infrastructure that lets our platform run AI agents for enterprise customers. This isn't traditional web app SRE — our agents execute arbitrary code in sandboxes, make unpredictable external API calls, and run for hours. Keeping this reliable, secure, and observable is the job. You'll be part of newly formed SRE team as one of the first team members. Infrastructure is currently owned collectively by product engineers — you'll take ownership, inherit real infrastructure (25+ Terraform modules, full OpenTelemetry pipeline, Prometheus/Grafana monitoring), and build the reliability practice from scratch. Your unit of ownership: platform reliability, infrastructure, observability, and incident response. You own sandbox infrastructure and capacity; the AI Platform Engineer owns sandbox behaviour and runtime logic. We're a growing product team scaling into multiple initiatives, each with a lead, engineers, a design engineer, and an AI-focused engineer.
What We're Looking For
- Distributed systems experience. You've designed and operated systems that scale. You understand failure modes, capacity planning, and the trade-offs 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 ensure network isolation between tenant workloads. Security is a default consideration, not an afterthought.
- Observability and incident response. You build monitoring and alerting that catches problems before customers do. When incidents happen, you lead structured responses, find root causes, and drive lasting fixes — not just restarts.
- Infrastructure as code and automation. You automate everything you can. You've worked with IaC tools, CI/CD pipelines, and container orchestration in production. Manual runbooks make you uncomfortable.
- Shipping and ownership. You don't just maintain systems — you improve them. You take ownership of reliability projects from proposal to production, and you measure the results.
- Judgment on where to invest. You'll decide what to automate first, where to invest in reliability vs. ship speed, and 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.
- Be comfortable with AI/ML production systems — understanding the unique reliability challenges of LLM-based applications.
- Have a product engineering background — you've built features and 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 want to build AI features — see AI Platform Engineer.
Our tech stack
- GCP (Cloud Run, GKE, GCS)
- Terraform, Docker
- Prometheus, Grafana, Loki, OpenTelemetry
- TypeScript and Python services (you'll read and occasionally modify application code, but deep language expertise isn't required)
- Postgres, Redis
How we work
- Initiative-driven. We organise around customer problems, not org charts. Problems surface through product feedback, competitive analysis, and direct customer conversations — then we prioritise, build, and ship weekly.
- Customer-obsessed. We solve real problems, not hypothetical ones. Features that don't move customer metrics get cut.
- Iterative by default. We ship small, learn fast, and never get attached to yesterday's code. This means things break sometimes — we fix forward.
- AI-first leverage. We use AI to move faster and focus human time where it matters most. If a tool can do it, a person shouldn't.
- Direct feedback. We give each other actionable feedback immediately. This can feel uncomfortable — we think that's worth it.
- Autonomy with accountability. We trust people to make decisions and hold them to outcomes, not process.
What we offer
- Unlimited AI budget. We don't just allow AI tools — we strongly encourage them. Want to try a new tool? Buy it. Want to automate part of your workflow? Do it.
- Autonomy to do your best work. Want to meet someone to learn from? Set it up. Want a mentor? Go get one. Want to fly out to talk to an important customer? Just ask.
- A real AI product with real customers. You're not building demos or internal tools. Enterprise customers use what you ship, and their feedback drives what you build next.
- A sharp, motivated team that values ownership and candour.
Compensation 250.000,- CZK / month with a meaningful equity component. You can trade salary for additional equity if you prefer more upside.
How we hire
We respect your time and aim to move fast:
- Hiring manager screen (30 min). We'll talk about systems you've built and operated, how you handle incidents, and whether there's mutual fit.
- Remote task (async, time-boxed, ~1 hour). A realistic infrastructure or reliability exercise — an incident response scenario, an IaC task, or a monitoring design challenge. Not LeetCode.
- Technical interview (Prague, ~1 hour). Meet the team. We'll go deeper on system design, security thinking, and incident response. No trick questions — we want to see how you reason about production systems.
- On-site trial day (2 days). Work on a real infrastructure problem with us and see how we operate. Fully compensated.
Compensation Range: €110K - €220K
Site Reliability Engineer (EU/UK Based - Remote) employer: duvo.ai
At our company, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to take ownership of their projects and drive meaningful change. As a Site Reliability Engineer, you'll have the unique opportunity to shape the reliability practices of our cutting-edge AI operations platform while working remotely from anywhere in the EU/UK. We offer competitive compensation, an unlimited AI budget for tools and resources, and a supportive environment that encourages continuous learning and professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Site Reliability Engineer (EU/UK Based - Remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common SRE scenarios. Think about how you'd handle incidents, manage infrastructure, and ensure security. We want to see your thought process, so be ready to explain your decisions clearly.
✨Tip Number 3
Show off your projects! Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart. It’s all about demonstrating your skills and passion for reliability engineering.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Site Reliability Engineer (EU/UK Based - Remote)
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for the role shine through! We want to see that you’re genuinely excited about the opportunity to work with us and tackle the challenges we face in building our AI operations platform.
Tailor Your Experience:Make sure to highlight your relevant experience in distributed systems, security, and observability. We’re looking for specific examples of how you've tackled similar challenges in the past, so don’t hold back on those details!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what really matters. Remember, we want to understand your skills and experiences without wading through fluff.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re proactive and keen to join our team!
How to prepare for a job interview at duvo.ai
✨Know Your Systems
Make sure you can talk confidently about distributed systems you've designed and operated. Brush up on failure modes, capacity planning, and the trade-offs between consistency, availability, and latency. This role is all about reliability, so showing your understanding of these concepts will impress.
✨Security is Key
Prepare to discuss your security mindset. Be ready to explain how you've managed enterprise data in sandboxed environments, configured KMS encryption, and ensured network isolation. Security isn't an afterthought here, so demonstrate that you prioritise it in your work.
✨Showcase Your Automation Skills
This role requires a strong focus on Infrastructure as Code and automation. Be prepared to share examples of how you've automated processes using IaC tools, CI/CD pipelines, or container orchestration. Highlighting your comfort with automation will show you're a great fit for their fast-paced environment.
✨Emphasise Ownership and Initiative
Talk about times when you've taken ownership of projects from proposal to production. They want someone who doesn't just maintain systems but actively improves them. Share specific examples of how you've measured results and made decisions on where to invest your time and resources.
