Software Engineer - Self Service Intelligence, SCC Eng
About this role
Millions of riders and drivers rely on Lyft every single day, and when unexpected issues arise, they need fast, clear, and frictionless resolutions. The Self-Serve Intelligence team addresses this core challenge by building AI-powered systems that autonomously resolve customer friction without requiring human agent involvement.
As a software engineer on this team, you will design and develop the backend services, APIs, and GenAI-driven products that power these automated customer experiences. You will collaborate closely with machine learning engineers, product managers, designers, and data scientists to ship new AI Agent capabilities and build robust evaluation pipelines.
The ideal person for this role brings strong engineering instincts, a genuine curiosity about applied AI, and the ability to navigate ambiguity in a rapidly evolving technological space. You will thrive here if you enjoy turning complex customer pain points into reliable, scalable software solutions.
What you will do
- Write well-crafted, well-tested, readable, and maintainable code across the team's services.
- Partner with senior engineers to design, build, and ship backend services and GenAI-powered products like AI Agents.
- Independently lead technical tasks from initial idea through to final 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 service architecture.
- Debug and improve system reliability while participating in incident resolution.
- Collaborate cross-functionally with product, design, data science, and operations to deliver shipped solutions.
What you need
- Proficiency in at least one general-purpose programming language such as Python, Java, or Go, with Python preferred.
- Familiarity with distributed systems, microservices, and building or consuming APIs in a service-oriented environment.
- Exposure to at least one operational or analytical data system like DynamoDB or Redis.
- Ability to write thorough, scalable, and clear design documentation.
- Capacity to learn and research new technologies rapidly to build scalable solutions.
- Experience using AI-assisted development tools responsibly, such as Claude Code, GitHub Copilot, Cursor, or AI agents.
- Strong written and verbal communication skills in English.
Nice to have
- 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
Skills and tech stack
Questions candidates ask
What kind of systems will I be building?
You will design and build backend services, APIs, and GenAI-powered products that combine robust engineering with applied AI to deliver reliable, scalable self-serve experiences. This includes shipping new AI Agent capabilities, building evaluation pipelines, and improving underlying backend services.
Who will I be working with on a daily basis?
Every day, you will partner with machine learning engineers, product, design, data science, and operations on high-impact projects. You will also work closely with senior engineers who will provide guidance on your workload and system designs.
What qualifications are preferred for this role?
Preferred qualifications include 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, AI agent frameworks, and familiarity with monitoring production services are also valued.