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For Companies At a Glance
- Tasks: Build and operate AI-native infrastructure for scalable, reliable systems.
- Company: Join Typeform, a leading form builder transforming customer interactions.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Experience in software or platform engineering with distributed systems.
The predicted salary is between 60000 - 80000 £ per year.
Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year—and integrates with essential tools like Slack, Zapier, and Hubspot.
About the Team
Typeform is evolving into an AI-native platform where intelligent agents, real-time systems, and large-scale model workflows power the next generation of customer interactions.
As a Platform Engineer – Infrastructure, you will design and operate the foundational infrastructure that enables these AI-powered systems to run reliably at scale. This includes building the deployment platforms, streaming systems, compute orchestration, and runtime environments required for agent-based architectures and modern AI workloads.
You will work at the intersection of platform engineering, distributed systems, and AI infrastructure, partnering closely with Backend, AI, and Product teams to ensure that complex systems—from agent streaming pipelines to novel deployment environments—are scalable, observable, and production-ready.
This role is ideal for an engineer who enjoys building deep infrastructure systems, thrives on solving complex reliability challenges, and wants to play a key role in enabling the next generation of intelligent software at Typeform.
Things you will do:
- Build and operate infrastructure for AI-native systems, including agent runtimes, model-powered services, and real-time workflows.
- Design scalable, reliable deployment platforms that enable engineering teams to ship complex services efficiently.
- Develop primitives for event-driven and streaming workloads supporting high-throughput AI systems.
- Build low-latency, real-time systems for asynchronous workloads, streaming pipelines, and model interactions.
- Partner with AI Engineering, Product Engineering, and Product Management teams to deploy and operate model-powered and agent-driven services.
- Ensure observability, monitoring, and operational excellence across all critical infrastructure.
- Establish best practices for reliability, performance, and operational ownership across the company.
What you already bring to the table:
- Several years of experience as a software, infrastructure, or platform engineer working with distributed systems.
- Strong experience building or operating cloud-native infrastructure and service platforms.
- Deep understanding of distributed systems, asynchronous architectures, and scalable service design.
- Experience working with containerized infrastructure and orchestration platforms such as Kubernetes.
- Strong programming experience in languages commonly used for infrastructure (Go, Python, Rust, or similar).
- Experience designing or operating systems with high reliability and performance requirements.
- Ability to collaborate effectively across teams and translate technical requirements into platform capabilities.
- Experience building infrastructure for AI or machine learning systems.
- Familiarity with streaming systems such as Kafka, Pulsar, or NATS.
- Experience supporting model serving, AI inference, or agent-based systems.
- Background working in a fast-growing SaaS or product-led company.
Typeform drives hundreds of millions of interactions each year, enabling conversational, human-centered experiences across the globe. We move as one team, empowering our collective efforts by valuing each individual’s unique perspective. This fosters strong bonds grounded in respect, transparency, and trust. We champion our diverse customer base by anticipating their needs and addressing their challenges with priority. Committed to excellence, we hold high expectations for ourselves and each other, continuously striving to deliver exceptional results.
We are proud to be an equal-opportunity employer. We celebrate diversity and stand firmly against discrimination and harassment of any kind—whether based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status. Everyone is welcome here.
Platform Engineer in London employer: Typeform
Contact Detail:
Typeform Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Typeform. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a project or two that showcases your experience with distributed systems or cloud-native infrastructure, make sure to highlight them in conversations or during interviews.
✨Tip Number 3
Prepare for technical challenges! Brush up on your knowledge of container orchestration and streaming systems. Being ready to tackle real-world problems will impress the hiring team.
✨Tip Number 4
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 the Typeform family.
We think you need these skills to ace Platform Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Platform Engineer role. Highlight your experience with distributed systems and cloud-native infrastructure, as these are key to what we do at Typeform.
Showcase Your Skills: Don’t just list your skills—demonstrate them! Use specific examples from your past work that show how you've built or operated scalable systems, especially in AI or machine learning contexts. We love seeing real-world applications!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it's necessary. Make it easy for us to see why you’re a great fit!
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’s super easy!
How to prepare for a job interview at Typeform
✨Know Your Infrastructure Inside Out
Make sure you brush up on your knowledge of cloud-native infrastructure and distributed systems. Be ready to discuss your experience with container orchestration platforms like Kubernetes, as well as any relevant programming languages such as Go or Python. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Showcase Your Problem-Solving Skills
Typeform is looking for someone who thrives on solving complex reliability challenges. Prepare examples from your past work where you tackled tough problems, especially in building scalable and reliable systems. Use the STAR method (Situation, Task, Action, Result) to structure your responses clearly.
✨Collaborate Like a Pro
Since this role involves partnering with various teams, be ready to discuss how you’ve effectively collaborated in the past. Highlight experiences where you translated technical requirements into actionable platform capabilities, and demonstrate your ability to communicate complex ideas simply.
✨Understand AI and Machine Learning Basics
As Typeform is evolving into an AI-native platform, having a solid understanding of AI and machine learning systems will set you apart. Brush up on your knowledge of streaming systems like Kafka or Pulsar, and be prepared to discuss how you’ve supported model serving or AI inference in previous roles.