As a Senior Software Engineer on the Foundational Infrastructure & Networking team, you will own the core routing, service mesh, and control planes that power hundreds of microservices processing millions of rides daily. This is an IC role with massive engineering leverage: your technical architecture, systems design, and performance optimizations will directly amplify the velocity of every software engineer across Lyft while ensuring platform resiliency at scale.
Responsibilities

• Architect & Scale Core Networking: Design, build, and optimize our service mesh, ingress/egress infrastructure, and edge routing capabilities using Envoy Proxy and custom control planes on AWS.
• Optimize High-Throughput Control Planes: Enhance load-balancing algorithms, service discovery, and dynamic scaling mechanisms across high-concurrency data and control planes running on Kubernetes.
• Drive Systems Reliability & Observability: Operationalize deep telemetry, metrics, and distributed tracing across our networking stack to drastically reduce mean-time-to-detect (MTTD) and resolution (MTTR).
• Hands-on Production Debugging: Lead complex technical investigations into cross-stack incidents spanning kernel parameters, cloud VPC network layers, DNS, and distributed microservice protocols.
• Technical Leadership & Mentorship: Elevate engineering rigor through RFC reviews, technical vision, incident response post-mortems, and mentoring engineers across the broader Infrastructure org.

Experience

• 6+ Years of Production Systems Experience: Proven track record building and operating massive-scale cloud infrastructure and networking platforms.
• Expertise in Cloud Networking & Protocols: Deep understanding of Linux networking, TCP/IP, DNS, gRPC, HTTP/2, load balancing, and AWS networking architecture (VPCs, NLBs, subnets, transit gateways).
• Service Mesh & Proxy Expertise: Hands-on experience building or operating large-scale proxy and mesh technologies (e.g., Envoy, Istio, Cilium, Nginx).
• Cloud & Container Infrastructure: Strong experience managing production Kubernetes clusters running on public cloud providers (AWS/GCP) using Infrastructure-as-Code tools (Terraform).
• Distributed Systems Troubleshooting: Demonstrated skill in isolating and debugging complex, multi-layered system failures under high throughput conditions.

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match 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 is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

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. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $136,000 - CAD $170,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.