Software Engineer - Self Service Intelligence, SCC Eng

Lyft; Ciudad de México; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Lyft is seeking a Software Engineer for the Self-Serve Intelligence team to build backend services and GenAI-powered products that autonomously resolve rider and driver issues. You will collaborate with ML engineers, product, design, data science, and operations on high-impact projects, from AI Agent capabilities to evaluation pipelines and robust APIs.

You should bring strong programming instincts, curiosity about applied AI, and comfort working through ambiguity in a rapidly changing space.

Formación

• Proficiency in a general-purpose language (Python, Java, Go); Python preferred.
• Familiarity with distributed systems and microservices.
• Experience building or consuming APIs in a service-oriented environment.
• Exposure to operational or analytical data systems (e.g., DynamoDB, Redis).
• Ability to write scalable, clear design documentation.
• Ability to learn new technologies rapidly and build scalable solutions.
• Ability to manage workload with guidance from senior engineers.
• Experience using AI-assisted development tools responsibly (e.g., Claude Code, GitHub Copilot).
• Willingness to work through ambiguity and deliver deployable solutions.
• Good written and verbal communication skills.

Responsabilidades

• Write well-crafted, well-tested, readable, and maintainable code.
• Design, build, and ship backend services and GenAI-powered products that resolve rider and driver issues.
• Independently lead tasks from idea to execution.
• Contribute to evaluation frameworks that measure GenAI-driven experiences.
• Build and extend APIs and data models within the team’s services.
• Debug and improve system reliability and participate in incident resolution.
• Learn and apply emerging AI capabilities to daily work.
• Collaborate with ML, product, design, data science, and operations to ship solutions.
• Participate in code reviews to ensure quality and share knowledge.
• Support knowledge sharing through brown bags and tech talks.

Conocimientos

Python

Distributed systems

APIs

Data systems

Design docs

Rapid learning

Workload mgmt

AI tools

Communication

Herramientas

DynamoDB

Redis

Descripción del empleo

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