Python Engineer, Kaizo

• You see the backend as a living ecosystem — where data flows cleanly, APIs hum in harmony, and nothing ships unless it’s rock-solid
• You don’t just write code; you craft systems that stay fast, scalable, and ready for real-world abuse — code that survives long after the PoC hype fades
• You’re energised by systems that process millions of events a day
• You gravitate toward clarity, performance, and good engineering hygiene
• And when someone says “We’re scaling this from prototype to production,” that’s when you shine
• ✅ 3+ years of experience building backend systems with Python
• ✅ Experience optimising Python services under real load — profiling, async, multiprocessing, CPU/I/O balancing
• ✅ Strong experience with Kafka or large-scale event-driven systems
• ✅ Solid engineering fundamentals: API design, testing, CI/CD, observability
• ✅ Curiosity about scalable AI/LLM systems and how to productionise them
• ✅ A collaborative, ownership-driven mindset — we value low-ego, high-impact engineers

Desirable

• We’re scaling fast — new features, new customers, new challenges — and our platform processes 200M+ events every single day
• You’ll join a tight-knit, senior engineering team building the next generation of Kaizo’s backend — fully powered by Python, from APIs to data pipelines to AI integrations
• You’ll own every stage of delivery:
• From experimenting quickly → to designing scalable services → to shipping production-grade systems you’re proud of
• You’ll also partner closely with our AI/Data Science team, making sure our models, data flows, and backend services work together seamlessly and safely
• If you love Python, distributed systems, and solving real scaling problems — this is your playground
• 🧠 Design and build RESTful APIs and backend services powering our product and analytics layers
• ⚙️ Develop Python features end-to-end — from zero → prototype → production
• 📡 Build and optimise event pipelines processing hundreds of millions of daily events using Kafka and other streaming tools
• 🧩 Drive performance improvements — batching, parallelisation, async patterns, backpressure, load optimisation
• 🔐 Apply strong security practices (OWASP) across everything you ship
• 🤖 Work with LLM providers (OpenAI, Anthropic, Groq, Vertex AI, DeepSeek) to design scalable AI service layers — batching, failover, retries, rate limiting
• 🤝 Partner closely with AI/Data Science to deploy ML models with fast, stable, production-ready interfaces
• 🪄 Work with Product Managers and engineering peers to architect solutions balancing speed, scale, and cost
• 🧰 Shape architectural decisions and evolve our Python and infrastructure tooling

• Start date: December 2025 – January 2026
• 1️⃣ Intro call with Jo, our Talent Partner
• 2️⃣ Deep-dive technical assessment + follow-up with Marc and Samuel
• 3️⃣ Conversation with Dominik, our CEO
• 4️⃣ Final team chat — meet the engineers, ask anything