Senior Software Engineer, Self-Serve Intelligence

Job Description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Every day, millions of riders and drivers depend on Lyft — and when something goes wrong, we want to make it right as fast as possible. The Self-Serve Intelligence team within Safety & Customer Care org is building the AI-powered systems that do exactly that: resolving rider and driver suboptimal experiences without agent involvement through intelligent solutions in AI Assist (e.g. AI Agents), automations, and self-serve workflows. We're building backend systems, APIs, and AI-powered products that fundamentally rethink how customers get help — combining robust engineering with GenAI to deliver reliable, scalable self-serve experiences. As a Senior Software Engineer on the Self-Serve Intelligence team, you will design, build, ship, and maintain backend services and AI-powered products (e.g. various AI Agents) that autonomously resolve customer suboptimal experiences. You'll own the full lifecycle — from system design and prototyping through production deployment and operational excellence — partnering with product, design, data science, and operations to deliver high-quality, reliable solutions at scale. Responsibilities: Design, build, ship, and maintain scalable backend services and GenAI-powered products (e.g. AI Agents) that resolve rider and driver suboptimal experiences autonomously Develop robust evaluation frameworks to measure and improve the quality and impact of GenAI-driven customer experiences Lead projects from idea to production, owning end-to-end system design, implementation, and operational health Write well-crafted, well-tested, readable, maintainable code Design and evolve APIs, data models, and service architectures that support rapid product iteration Rapidly adopt and integrate emerging AI capabilities to accelerate development velocity across the team Incorporate considerations for edge cases, failure modes, and business context into system design Participate in code and architecture reviews to ensure quality and distribute knowledge Own system reliability — monitor, debug, and improve service health, latency, and availability Proactively participate in resolving ongoing incidents Unblock, support, and effectively communicate across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing engineering and AI best practices Experience: 5+ years of software engineering industry experience Strong backend engineering fundamentals — designing, building, and operating distributed systems and microservices in production Hands-on experience with LLMs, agentic workflows, or building AI Agents — we value depth of A

Required Skills