Principal Software Engineer, AI & Matching

Role Overview

• Lead the architecture and technical direction for matching and AI agent systems that power personalization, discovery, recommendations, and user assistance across Bumble**
• Design and build high-scale, low-latency production services for retrieval, ranking, recommendations, decisioning, and agent orchestration
• Drive the evolution of Bumble’s matching architecture, including how models, business logic, real-time signals, and product experiences work together in production
• Partner closely with ML engineers and applied scientists to productionize models for training, online inference, evaluation, and continuous improvement
• Help define how AI agents can be safely and effectively integrated into the Bumble experience, including tool use, orchestration, memory, and decision boundaries
• Make strong technical tradeoffs across classical software, machine learning, and LLM-based approaches based on latency, quality, cost, safety, and user impact
• Set engineering standards for system design, reliability, experimentation, observability, and responsible AI in user-facing intelligent systems
• Collaborate cross-functionally with Product, Design, Trust & Safety, Data Science, and Infrastructure to deliver end-to-end user experiences from concept to production
• Mentor senior and staff-level engineers, raise the technical bar across the organization, and influence architecture well beyond your immediate team

Requirements

• Deep expertise as a software engineer building large-scale distributed systems, with significant experience in consumer-facing or marketplace products
• Strong track record designing and operating production recommendation, matching, search, ranking, personalization, or decisioning systems
• Experience building systems that integrate machine learning models into real-time product experiences, including online serving, experimentation, and monitoring
• Strong understanding of the tradeoffs between traditional software, ML systems, and LLM/agent-based architectures, and when each is the right tool
• Experience building or scaling AI-native product capabilities, such as copilots, assistants, tool-using agents, or conversational/intelligent workflows
• Ability to operate at both the architectural and implementation level: setting long-term direction while staying close enough to the code and systems to drive execution
• Proven ability to influence technical strategy across multiple teams and deliver in complex, ambiguous problem spaces
• Strong product instincts and the ability to translate user needs into robust technical systems that create measurable business and member impact
• Commitment to building AI systems responsibly, with attention to privacy, safety, transparency, and fairness
• Typically requires 12+ years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
• High level of AI fluency, with the ability to both apply AI tools in your own work and guide teams in embedding AI into systems and workflows at scale
• You role model Bumble values such as Courage and Respect, collaborate effectively across disciplines, take ownership of outcomes, and see work through from insight to measurable impact with an agile mindset

Tech Stack

• Distributed Systems