Senior Backend Engineer, AI & APIs Orchestration

Lyft; Toronto (OH); Hybrid; USD 97,000 - 121,000; Full time

Benefits offered by this job

Health coverage

Mental health benefits

Family building benefits

Child care benefits

Lyft Health Savings Account

RRSP matching

Paid time off (PTO)

Parental leave

Commuter benefits

Ride credits

Hybrid work model

Job summary

Lyft is seeking a Backend Engineer for the Applied AI team in Toronto. You will build infrastructure connecting Lyft to AI ecosystems and architect APIs for third-party agents and multimodal interfaces.

Ideal candidates have 5+ years of software engineering experience, strong Python/Go skills, and cloud/database expertise. The role emphasizes collaboration across product, data science, and operations, with a hybrid in-office schedule.

Qualifications

• BS/MS in Computer Science or related field; equivalent practical experience.
• 5+ years of software engineering/production infrastructure experience.
• Proficient in Python and Go; experience with cloud platforms and databases.

Responsibilities

• Establish engineering best practices and patterns; uplift team craft and drive excellence.
• Drive high-impact projects and deliver scalable system designs.
• Mentor engineers and review code for quality and maintainability.
• Collaborate across product, data science, analytics, and operations.
• Explain trade-offs and manage priorities and deadlines.

Skills

Python

Go

AWS

GCP

Azure

PostgreSQL

DynamoDB

OOP

Data structures

Algorithms

LangChain

Vector DB

API design

Collaboration

Education

BS/MS in Computer Science

Equivalent practical experience

Job description

Lyft is seeking a Backend Engineer for the Applied AI team in Toronto. You will build infrastructure connecting Lyft to AI ecosystems and architect APIs for third-party agents and multimodal interfaces.

Ideal candidates have 5+ years of software engineering experience, strong Python/Go skills, and cloud/database expertise. The role emphasizes collaboration across product, data science, and operations, with a hybrid in-office schedule.