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Distributed Systems Software Engineer Jobs in California

Picarro, Inc

Systems Software Engineer

Santa Clara, CA · On-site

$120K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build reliable communication interfaces for distributed instrument systems * Collaborate with ... Programmable Logic Controllers (PLCs) * Strong understanding of instrument communication protocols:

Picarro, Inc

Systems Software Engineer

Santa Clara, CA · On-site

$120K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build reliable communication interfaces for distributed instrument systems * Collaborate with ... Programmable Logic Controllers (PLCs) * Strong understanding of instrument communication protocols:

Archil

Distributed Systems Engineer

San Francisco, CA · On-site

As a Distributed Systems Engineer, you will work across the stack to solve problems, build ... Archil is a software company that develops cloud storage software that enables organizations to ...

Nvidia

Principal Systems Software Engineer

Santa Clara, CA

$158K - $212K/yr

NVIDIA is seeking a Sr. Principal Systems Software Engineer for the Apache Spark Acceleration group ... Collaborate with distributed systems teams to craft solutions to distributed processing problems ...

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Distributed Systems Software Engineer information

What are the key skills and qualifications needed to thrive as a distributed systems software engineer?

To thrive as a Distributed Systems Software Engineer, you need strong programming skills (often in languages like Java, Go, or C++), a deep understanding of algorithms, networking, and distributed computing concepts, typically supported by a degree in computer science or a related field. Familiarity with tools and frameworks such as Kubernetes, Apache Kafka, Docker, and cloud platforms (AWS, GCP, or Azure) is highly valued, as are certifications in cloud or devops technologies. Excellent problem-solving, teamwork, and communication skills help you design scalable solutions and collaborate across teams. These skills are crucial for building reliable, efficient, and scalable distributed systems that power modern applications and services.

What is the difference between Distributed Systems Software Engineer vs Cloud Software Engineer?

AspectDistributed Systems Software EngineerCloud Software Engineer
Required CredentialsBachelor's in CS or related, experience with distributed architecturesBachelor's in CS, experience with cloud platforms (AWS, Azure)
Work EnvironmentDevelops scalable distributed applications, often in data centers or on-premisesBuilds and maintains cloud-based solutions, deploying on cloud platforms
Employer & Industry UsageTech companies, data centers, distributed computing firmsCloud service providers, SaaS companies, enterprises adopting cloud
Search & Comparison IntentUnderstanding roles in distributed architectureComparing cloud-focused development roles

While both roles involve building scalable software, a Distributed Systems Software Engineer focuses on designing and implementing distributed architectures, whereas a Cloud Software Engineer specializes in deploying and managing applications on cloud platforms. The roles often overlap but differ mainly in their environment and specific technical focus.

What are the typical challenges faced by distributed systems software engineers when ensuring system reliability?

Distributed Systems Software Engineers often encounter challenges like handling network partitioning, ensuring data consistency across nodes, and effectively managing system failures. They need to design resilient architectures that can recover gracefully when components fail, and implement robust monitoring to detect issues early. Collaborating closely with DevOps, QA, and other engineering teams is crucial to address these challenges and maintain high availability and performance in complex, distributed environments.

What is a distributed systems software engineer?

Distributed Systems Software Engineers are professionals who design, develop, and maintain software that runs across multiple computers or servers, working together to achieve a common goal. They build systems that are reliable, scalable, and efficient, often handling large volumes of data and user requests. Their work involves solving challenges related to network communication, data consistency, fault tolerance, and system coordination. These engineers frequently use technologies like cloud computing platforms, message queues, and databases to ensure smooth operation across distributed environments.
What are popular job titles related to Distributed Systems Software Engineer jobs in California? For Distributed Systems Software Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Distributed Systems Software Engineer jobs in California look for? The top searched job categories for Distributed Systems Software Engineer jobs in California are:
Distributed Systems Software Engineer jobs near you
Infographic showing various Distributed Systems Software Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Staff+ Software Engineer, Infrastructure (Distributed Systems)

Anthropic

San Francisco, CA • On-site

$203K - $241K/yr

Full-time

Posted 5 days ago

Job description

About the role

Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models, including data pipelines, some of the largest Kubernetes clusters in the world, along with the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff+ Software Engineer on our Infrastructure team, you'll independently scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work closely with research and product teams to understand their needs and build systems that keep pace as those needs evolve.

  • Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This lets us match you with the team where you'll have the most impact.
Key responsibilities
  • Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system
  • Make architectural decisions that shape the foundation of infrastructure other engineers and teams build on
  • Drive alignment on technical direction across multiple teams, working through ambiguous problem spaces
  • Partner with research and product teams to understand their infrastructure and compute needs, and translate them into technical designs
  • Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow
  • Set technical strategy and standards for your team's infrastructure
  • Build and improve operational processes, such as incident response, postmortems, and on-call rotations, that help the team learn from every incident
  • Mentor other engineers and help raise the technical bar for the team
Minimum qualifications
  • Experience designing, building, and operating large-scale distributed systems or infrastructure in production
  • A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
  • Experience making architectural decisions that other engineers and teams build on top of
  • Strong software engineering fundamentals and proficiency in at least one programming language (for example, Python, Rust, Go, or Java)
  • Experience with modern cloud infrastructure, including Kubernetes and infrastructure-as-code, on AWS and/or GCP
  • Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders
Preferred qualifications
  • 10+ years of software engineering experience, not including internships
  • Experience with machine learning infrastructure, such as GPUs, TPUs, or Trainium, and associated networking infrastructure like NCCL
  • Low-level systems experience, such as Linux kernel tuning or eBPF
  • Background in security or privacy engineering best practices
  • Prior experience as a technical lead or mentor for other engineers

Deadline to apply: None. Applications are reviewed on a rolling basis.

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