Staff Software Engineer – Service Mesh & Networking
- Sunnyvale, CA, United States
- San Francisco, CA, United States
$232,000 to $258,000 USD / year
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Job details
- Pay
- $232,000 to $258,000 USD / year
- Experience
- 8+ years of software engineering experience.
- Posting language
- English
- Posted
Original job description
About the Role Every service at Uber relies on the service mesh to find, reach, and trust the services it depends on, and the 1M+ concurrent trips Uber supports depend on it. The Service Mesh team builds and operates this layer across Uber's global infrastructure, where every millisecond the mesh adds contributes to the critical path of user-facing requests, efficiency gains translate directly into compute capacity, and every change must be designed to roll out safely. As a Staff Software Engineer on the team, you will set technical direction for the proxy and networking infrastructure that carries Uber's service-to-service traffic. You will own problems end to end, from design through production rollout and long-term operation, working across Uber's security, network, compute, and storage stacks and with the product engineering teams whose services run on the mesh. What You'll Do
- Define the multi-quarter technical roadmap for the service mesh forwarding layer, including how core components of a live system evolve incrementally while traffic keeps flowing.
- Drive down the latency and compute cost of the forwarding path, from proxy performance to smarter load balancing across hosts and zones, and roll out improvements safely.
- Evolve the forwarding layer toward a horizontally scalable, compartmentalized architecture so routing state and failures stay contained as the mesh grows.
- Strengthen service identity and authorization in the mesh without regressing tail latency.
- Build observability that makes the mesh explainable, from request-level visibility to clear signals for service owners and on-call engineers.
- Partner with product engineering teams and the teams behind Uber's security, network, compute, and storage stacks to turn their needs into platform capabilities.
- Lead through influence by writing design docs, setting standards, leading incident response and postmortems, mentoring engineers, and introducing automation, including AI-based workflows, where it reduces toil.
About the Team The Service Mesh team routes and load balances traffic between all Uber services across on-premises data centers and multiple public clouds, providing discovery, overload protection, traffic shifting, and service identity on both proxied and peer-to-peer paths. We follow a few core principles: failures stay contained, changes are staged, observed, and reversible, and efficiency gains fund new capabilities. Our direction is a single Envoy-based forwarding layer that runs natively on Kubernetes and aligns with open standards such as the Gateway API. The Service Mesh team is part of the Platform Engineering Team (PET), which includes Compute, Network, Storage, Reliability and Hardware Engineering, Corporate IT, and more. PET's mission is to "Empower One Uber to innovate by building a world-class foundation that accelerates growth at scale."
Basic Qualifications
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
- 8+ years of software engineering experience.
- Proficiency in one or more of Go, C++, or Java.
- Experience building and operating large-scale, latency-sensitive distributed systems or infrastructure in production.
- Experience leading multi-team engineering projects through their full lifecycle, working across infrastructure and product teams.
Preferred Qualifications
- Strong working knowledge of networking protocols such as HTTP/2, gRPC, and TLS, as well as load balancing and traffic management.
- Experience with proxies or service mesh technologies such as Envoy, and with Kubernetes networking.
- Experience with service identity, authentication, and authorization, such as mTLS and SPIFFE.
- Experience with safe change management for critical infrastructure, including staged rollouts, backward compatibility, rollback, and incremental migrations that keep old and new paths interoperable.
- Contributions to open-source projects such as Envoy or gRPC.
- A track record of mentoring engineers and raising the hiring bar.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
More about this job
Skills
- Incident response
- Coaching
- Computer science
- Go
- C++
- Oracle Java
- Kubernetes
- Change management
- Collaboration