Principal Software Engineer, AI & Matching

Bumble·Удалённо·Удалённо·2 мес. назад·280 000 – 320 000 $/год

At Bumble, our mission is to create a world where all relationships are healthy and equitable. Our AI & Matching team plays a critical role in bringing this to life- powering the intelligence behind the experiences that help people build meaningful connections, safely and confidently.

As a Principal Software Engineer, AI & Matching, you will define and build the next generation of systems that make Bumble smarter, more adaptive, and more helpful for our members. This is a highly technical leadership role focused on designing and scaling core matching, recommendation, retrieval, ranking, and agentic AI systems that directly shape the user experience.

You will work across engineering, machine learning, product, and trust & safety to turn advances in AI into production systems that are reliable, low-latency, and deeply aligned with user value. This role is ideal for someone who combines strong software engineering fundamentals with deep experience building ML-powered products and a passion for applying AI to real user problems at scale.

What you’ll do

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

About you

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