Software Engineer - Self Service Intelligence, SCC Eng

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 to get where they're going. When something goes wrong along the way, they expect us to make it right — quickly, clearly, and without friction. How fast and how well we resolve those moments shapes whether people keep choosing Lyft.

The Self-Serve Intelligence team, within the Safety & Customer Care org, is composed of engineers building the AI-powered systems that do exactly that: resolving rider and driver suboptimal experiences without agent involvement through AI Assist (e.g. AI Agents), automations, and self-serve workflows.

Our goal is to make getting help feel effortless. We design and build backend services, APIs, and GenAI-powered products that combine robust engineering with applied AI to deliver reliable, scalable self-serve experiences.

We are looking for a highly motivated, collaborative, team-focused and technically strong Software Engineer to join our Self-Serve Intelligence team. As a member of this team, you will build the services and AI-powered products that resolve customer issues autonomously.

Every day, you'll partner with machine learning engineers, product, design, data science, and operations on high-impact projects — from shipping new AI Agent capabilities, to building the evaluation pipelines that keep their quality high, to improving the backend services underneath them.

You'll bring strong engineering instincts, genuine curiosity about applied AI, and a willingness to work through ambiguity in a space that changes month to month.

Responsibilities

Write well-crafted, well-tested, readable, and maintainable code

Partner with senior engineers to design, build, and ship backend services and GenAI-powered products (e.g. AI Agents) that resolve rider and driver suboptimal experiences

Independently lead tasks from idea to execution

Contribute to evaluation frameworks that measure and improve the quality of GenAI-driven customer experiences

Build and extend APIs and data models within the team's services

Debug and help improve the reliability of the systems you work on, and participate in resolving ongoing incidents

Learn and apply emerging AI capabilities to your day-to-day work

Partner with machine learning, product, design, data science, and operations to turn customer pain points into shipped solutions

Participate in code reviews to ensure code quality and distribute knowledge

Participate in knowledge sharing by supporting brown bags, tech talks, and championing appropriate tech and engineering best practices

Experience

Proficiency in at least one general-purpose programming language (e.g., Python, Java, Go); Python preferred

Familiarity with distributed systems and microservices

Familiarity with building or consuming APIs in a service-oriented environment

Exposure to at least one operational or analytical data system (e.g., DynamoDB, Redis, etc.)

Ability to write thorough, scalable, and clear design documentation

Ability to learn and research new technologies rapidly and build scalable solutions to tackle problems

Ability to manage your own workload with guidance from senior engineers

Experience using AI-assisted development tools responsibly (e.g. Claude Code, GitHub Copilot, Cursor, AI agents)

Willingness to work through ambiguity, developing deployable solutions to complex problems

Good written and verbal communication skills

Preferred qualifications

Hands-on exposure to LLMs, agentic workflows, or building AI Agents — through work, internships, coursework, or personal projects

Experience with prompt engineering, model evaluation pipelines, or AI agent frameworks

Familiarity with monitoring and debugging production services

Please submit your resume in English.