Platform Software Development Engineer

At Lyft, our purpose is to serve and connect. Lyft's AI Infrastructure and Tools Team is building the next generation of AI-powered development tools and foundational infrastructure. Our team is responsible for building the foundational layer that enables software engineers to integrate large language models seamlessly into their workflows. We provide standardized AI infrastructure, frameworks, and tooling that empower software developers to build AI features quickly while maintaining quality, safety, and cost efficiency.
We are growing rapidly and are seeking engineers to create an exceptional AI-enabled development experience across Lyft, contributing directly to the company's innovation velocity and competitive advantage in the AI era.
Key traits for success in this role include a passion for AI/ML infrastructure, developer experience, and automation; a quick learning ability in rapidly evolving AI technologies; and an eagerness to drive cross-functional AI initiatives. You'll be joining a team of passionate and supportive colleagues at the forefront of AI infrastructure.
As a Software Engineer on the AI Infrastructure & Developer Experience team at Lyft, you will design and build the foundational infrastructure that enables AI development at scale. You'll create frameworks for LLM integration, build intelligent agents for developer workflows, and establish best practices for AI safety, observability, and cost management. You'll collaborate across teams to democratize AI capabilities while ensuring reliability, security, and responsible AI usage. Your work will directly impact how every engineer at Lyft leverages AI from AI-assisted coding to automated upgrades to data analysis.
Design, build, and maintain AI infrastructure platforms including LLM gateways, prompt management systems, vector databases, and agent orchestration frameworks.
Build intelligent agents and AI-powered automation to enhance developer workflows across the software development lifecycle (code generation, testing, review, documentation, incident response).
Develop centralized automation workflow services and tools focused on an easy to use, streamlined, and user friendly UI experience.
Implement observability, monitoring, and cost management systems for AI infrastructure and LLM usage across the organization.
Plan and execute high-level cross-team AI infrastructure projects from inception to delivery, including model evaluation pipelines and AI safety guardrails.
Partner with ML Platform, Infrastructure, and product engineering teams to understand AI use cases, debug integration issues, and design scalable AI solutions.
Establish best practices and golden paths for LLM integration, prompt engineering, RAG implementations, and agent development.
Write well-crafted, well-tested, readable, and maintainable code for AI infrastructure components.
Lead incident responses for AI infrastructure issues, mentor the team on operational best practices, and implement long-term systemic fixes.
Build internal tooling for prompt testing, model comparison, AI performance benchmarking, and cost optimization.
Participate in the team's on-call rotations for AI infrastructure systems.
Mentor engineers across the organization on AI infrastructure best practices and responsible AI development.
Bachelor's degree in Computer Science or a related field, or equivalent experience.

• 3+ years of experience in software development, distributed systems, and infrastructure engineering.
• Experience building or integrating with AI/ML systems, LLM APIs (OpenAI, Anthropic, etc.), or AI infrastructure platforms.
• Strong understanding of LLM capabilities, limitations, prompt engineering, and AI safety considerations.
• Experience with API design, SDK development, and building developer-facing platforms or frameworks.
• Proficiency in Python and/or Go for building scalable AI infrastructure and tooling.
• Familiarity with vector databases, using embedding models, and RAG architectures.
• Experience with observability tools, distributed tracing, and monitoring systems.
• Ability to write clear technical documentation and design specifications for AI systems.

~ Bonus:

• Experience building AI agents, multi-agent systems, or agentic workflows.
• Hands-on experience with agent frameworks (LangChain, LangGraph, ReAct, etc.) or building custom orchestration systems.
• Experience with fine-tuning, model evaluation, or AI practices.
• Familiar with front-end frameworks and UI design.
• Background in developer experience, developer tools, or platform engineering.
• Experience implementing AI safety measures, content filtering, or guardrails.
• Contributions to open-source AI infrastructure projects.
• Knowledge of responsible AI practices, bias mitigation, and AI governance.

Extended health and dental coverage options, along with life insurance and disability benefits
Family building benefits
Child care and pet benefits
Access to a Lyft funded Health Care Savings Account
RRSP plan to help save for your future
In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.