Senior Product Engineer, Leadtech

• Python fluency, you can quickly build and utilise a wide range of libraries when the task calls for it
• 2–5 years of full-stack experience in a high-output team. You know how to balance speed with quality and when to choose one over the other
• Deep TypeScript & React proficiency on the frontend (Hooks, Context API, Vite, Shadcn UI) and backend (Node.js, Express, REST APIs, PostgreSQL)
• You have taste. You can distinguish between good and bad UX, and you can share examples to demonstrate it
• You’re AI-native. You reach for agents by default, understand MCP and agentic orchestration patterns, and have built guardrails to trust them more and more. Python proficiency for rapid prototyping is a must
• You’re self-driven and business-aware. You care about solving real problems and moving the needle on metrics, not just shipping features. Give you context, and you’ll find the leverage

Desirable

• As part of the AI-LAB team of MAU, as a Senior Product Engineer, you will be instrumental in building a multiplatform AI-powered document system serving hundreds of thousands of users every month
• We need a Product Engineer who ships end-to-end: someone who thinks like a product owner, codes like a craftsperson, and reaches for AI-native tooling by default
• Build and maintain the core multiplatform systems. You’ll own features end-to-end, from idea to production, React frontends, Node.js/Express backends, and PostgreSQL, Databricks integration & data layers
• Ship to learn. Proactively instrument features, measure impact, seek user feedback, and iterate or kill based on what you discover. You treat metrics as a compass, not a report card
• Design and orchestrate agentic AI workflows using modern frameworks (LangGraph, Claude Agent SDK, MCP protocols) and integrate LLMs into product features via prompt chains, tool calling, and function execution
• Collaborate with engineers, designers, and leadership to shape the product roadmap. You’ll have a real voice in what gets built and why
• Build, maintain, and extend automation pipelines and connect them with AI agents, external APIs, webhooks, and cloud services on GCP
• Contribute to database schema design (PostgreSQL, BigQuery), build and maintain RESTful APIs, and help manage our cloud infrastructure on Google Cloud Platform