Staff Software Engineer, Bee AI

At Bumble, we’re on a mission to create a world where all relationships are healthy and equitable. The Bee AI team is reimagining how people meet by introducing an intelligent, AI-powered layer on top of Bumble Date - helping members connect in more curated, thoughtful, and human ways, while preserving the magic of matching and conversation at the core of the product.

As a Staff Software Engineer, you’ll play a pivotal role in shaping this next generation of connection. Bee AI is already live and evolving quickly. If you’d like a glimpse into the experience we’re building, you can explore a recent preview here: https://www.instagram.com/p/DVwmOw_jKUf/. We’re now scaling both the ambition and the systems behind it - building intelligent agents that guide conversations, enhance matchmaking, and continuously learn from interaction patterns. You’ll help define how AI shows up responsibly and meaningfully in people’s dating experiences, role modelling our values of Curiosity and Courage as you explore new frontiers.

This is a highly impactful individual contributor role with broad influence across engineering, product, and data. You’ll operate as a technical leader, setting direction for how we build, evaluate, and scale AI agents - while fostering a culture that collaborates with purpose, takes ownership, and sees ideas through to real-world impact.

• Lead the design and evolution of AI-powered backend systems that support conversation guidance, matchmaking, and personalised user experiences within Bee AI

• Architect and scale agent-based systems, including prompt management, context orchestration, and evaluation frameworks, to ensure high-quality, reliable AI interactions

• Establish best practices for building, testing, monitoring, and iterating on AI agents, creating a repeatable and scalable development lifecycle across the team

• Drive experimentation and prototyping of new AI capabilities, translating early concepts into production-ready systems that deliver measurable user value

• Partner cross-functionally with Product, Data, and Trust teams to shape AI-driven features that are both innovative and responsible, demonstrating Respect in how technology impacts people

• Contribute deep expertise in Python (including PydanticAI) and Google Cloud Platform (GCP) to build robust, scalable, and observable services

• Define and implement evaluation strategies for LLM-powered systems, including offline and online metrics, human-in-the-loop validation, and continuous improvement loops

• Act as a technical advisor and thought leader, influencing architecture and long-term strategy across teams while embodying an agile mindset and taking ownership of outcomes