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Sr Staff Software Engineer - Kubernetes

Uber

Sr Staff Software Engineer - Kubernetes

Uber

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Flexible Hours

Learning

Equity

Parental Leave

Required Skills

React

Python

TypeScript

About the Role

We are seeking a highly experienced Senior Staff Engineer to lead the technical strategy and execution for our Compute Platform team, with a focus on Kubernetes orchestration and cloud-native infrastructure. As a Senior Staff Engineer, you are the principal architect of this ecosystem. You will own the technical evolution of our global Kubernetes footprint, solving the "hard problems" of multi-tenancy, extreme scale, and cloud-native efficiency. We aren't looking for a maintainer; we're looking for a visionary who has seen Kubernetes break at scale and knows exactly how to build it stronger.

As a senior technical leader, you will define architectural direction, guide large-scale initiatives, and mentor engineers while collaborating across product and infrastructure organizations.

What the Candidate Will Do ----:

  1. Own the technical vision, architecture, and strategy for the global compute platform org.
  2. Define and execute the roadmap for our compute platform, focusing on scalability, performance, and efficiency.
  3. Drive architectural decisions and set technical direction for compute scheduling, resource allocation, and container orchestration systems.
  4. Ensure high availability and reliability of the compute platform through best-in-class observability, automation, and incident response practices.
  5. Drive adoption of best practices in scalability, availability, and security for multi-tenant compute environments.
  6. Evaluate emerging technologies in cloud-native ecosystems and guide their integration into the platform.
  7. Partner with product and infrastructure teams to deliver high-impact, cross-organizational initiatives.
  8. Mentor and coach engineers, helping grow their technical depth and leadership skills.
  9. Influence company-wide engineering standards and practices.

---- Basic Qualifications ----

  1. 10+ years of software engineering experience, including expertise in distributed systems or infrastructure engineering.
  2. Deep expertise in Kubernetes internals, container runtimes, and cloud-native compute platforms.
  3. Strong background in containerization, resource scheduling, and cluster management at scale.
  4. Hands-on experience with performance tuning, reliability engineering, and cost optimization in compute environments.
  5. Excellent leadership, communication, and organizational skills, with a track record of building and mentoring high-performing teams.
  6. Strong coding proficiency in one or more languages such as Go, Java, or Python.
  7. Demonstrated ability to drive cross-functional technical initiatives and deliver impactful results.

---- Preferred Qualifications ----

  1. Experience with hybrid cloud or multi-cloud compute environments.
  2. Contributions to open-source Kubernetes or CNCF projects.
  3. Familiarity with modern stateful data infra and ML platforms running on top of compute infrastructure.
  4. Knowledge of emerging compute paradigms such as serverless, GPU scheduling, or federated orchestration.
  5. Prior experience working in fast-paced, large-scale environments with mission-critical workloads.
  6. Experience mentoring engineers at staff+ level.
  • For Sunnyvale, CA-based roles: The base salary range for this role is USD**$267,000 per year**
  • USD**$297,000 per year**.

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. More details can be found at the following link https://jobs.uber.com/en/benefits.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

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.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

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About Uber

Uber

Uber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.

10,001+

Employees

San Francisco

Headquarters

$120B

Valuation

Reviews

3.1

10 reviews

Work Life Balance

4.2

Compensation

2.3

Culture

3.5

Career

2.0

Management

2.5

45%

Recommend to a Friend

Pros

Flexible hours and schedule

Meeting different people and cultures

Make your own hours

Cons

Inconsistent and low pay

Safety concerns with passengers

Traffic and difficult drivers

Salary Ranges

23,534 data points

Mid/L4

Mid/L4 · Data Analyst

3 reports

$209,300

total / year

Base

$161,000

Stock

-

Bonus

-

$203,580

$209,300

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 80%

Neutral 20%

Negative 0%

Interview Process

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Phone Screen

5

Case Study/Analytics Test

6

Final Loop/Panel Interview

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Case Study

Technical Knowledge