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Senior Distributed Systems Engineer Jobs in California

Fluidstack

Distributed Systems Engineer

San Francisco, CA · On-site

$208K - $269K/yr

Distributed systems and data pipeline engineering. Time-series observability stacks (Prometheus, Thanos, VictoriaMetrics). API design and versioning at scale. Workflow and orchestration engines ...

IonQ

Senior Staff Distributed Systems Engineer

Santa Clara, CA · On-site

$122K - $167K/yr

We are looking for a deeply hands-on Senior Staff Distributed Systems Engineer to join the team building IonQ's Network and Security Platform. You will own the backend services - ingestion pipelines ...

Fluidstack

Distributed Systems Engineer

San Francisco, CA · On-site

$175 - $300/hr

Distributed systems and data pipeline engineering. Time-series observability stacks (Prometheus, Thanos, VictoriaMetrics). API design and versioning at scale. Workflow and orchestration engines ...

Enexus Global

Golang Developer

Fremont, CA · On-site

We are seeking a Senior Distributed Systems Engineer with deep expertise in designing, building, and scaling highly available distributed systems. You will play a key role in architecting resilient ...

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Senior Distributed Systems Engineer information

See California salary details

$55.3K

$123.1K

$173.7K

How much do senior distributed systems engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for senior distributed systems engineer in California is $123,099.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,100.00 and $141,100.00 per year, depending on experience, location, and employer.

What is a senior distributed systems engineer?

Senior Distributed Systems Engineers are experienced professionals who design, build, and maintain large-scale computing systems that run across multiple machines or locations. They focus on ensuring reliability, scalability, and performance of distributed applications, often dealing with challenges like data consistency, fault tolerance, and network latency. These engineers typically have deep expertise in distributed computing principles, programming languages, and cloud infrastructure. They also mentor junior team members and help architect robust solutions for complex technical problems.

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

A Senior Distributed Systems Engineer requires deep expertise in computer science fundamentals, scalable system architecture, and proficiency in programming languages such as Java, Go, or Python, often supported by a relevant degree and significant experience in distributed systems. Familiarity with tools like Kubernetes, Docker, Kafka, and cloud platforms (AWS, GCP, or Azure) is typically expected, along with knowledge of monitoring and CI/CD pipelines. Strong problem-solving, communication, and leadership skills help in tackling complex engineering challenges and collaborating across teams. These skills are crucial for designing robust, scalable, and reliable systems that support organizational growth and high availability.

What are some common challenges senior distributed systems engineers face when designing scalable systems?

Senior Distributed Systems Engineers often encounter challenges such as managing data consistency, ensuring fault tolerance, and minimizing latency across multiple nodes. Balancing trade-offs between availability and partition tolerance (as outlined by the CAP theorem) is a frequent consideration. Additionally, coordinating between development and operations teams to maintain system reliability and efficiently resolve issues that arise in production environments is crucial. Strong communication skills and a deep understanding of distributed architectures help address these complexities effectively.

What is the difference between Senior Distributed Systems Engineer vs Cloud Solutions Architect?

AspectSenior Distributed Systems EngineerCloud Solutions Architect
CredentialsBachelor's/Master's in CS or related, experience with distributed systemsBachelor's/Master's in CS, IT, or related, cloud certifications (AWS, Azure)
Work EnvironmentDesigning, developing, and maintaining distributed systems in tech companiesDesigning cloud infrastructure solutions for clients or internal teams
Industry UsageTech, finance, e-commerce, and enterprise sectorsIT consulting, cloud service providers, enterprise IT departments

The Senior Distributed Systems Engineer focuses on building and optimizing distributed computing systems, while the Cloud Solutions Architect designs cloud infrastructure solutions. Both roles require technical expertise and often overlap in cloud environments, but their primary responsibilities differ in scope and focus.

What are the most commonly searched types of Distributed Systems Engineer jobs in California?

The most popular types of Distributed Systems Engineer jobs in California are:

What are popular job titles related to Senior Distributed Systems Engineer jobs in California?

For Senior Distributed Systems Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Senior Distributed Systems Engineer jobs in California look for?

The top searched job categories for Senior Distributed Systems Engineer jobs in California are:

What cities in California are hiring for Senior Distributed Systems Engineer jobs?

Cities in California with the most Senior Distributed Systems Engineer job openings:

Senior Distributed Systems Engineer jobs near you
Infographic showing various Senior Distributed Systems Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 7% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $123,099 per year, or $59.2 per hour.

Distributed Systems Engineer

Fluidstack

San Francisco, CA • On-site

Full-time

Re-posted 17 days ago

Job description

Job Summary:
Fluidstack is focused on delivering compute infrastructure for AI, aiming to expand human freedom through technology. The Distributed Systems Engineer will own the observability platform and build critical infrastructure tools that ensure seamless operation and management of the company's hyperscale fleet.
Responsibilities:
• Own the observability platform. Build and operate the data pipelines, decoration and correlation engine, and healthcheck framework that make the fleet legible — from site down to device and link. No other team should need to scrape production directly to answer a question.
• Define and build the API surface for infrastructure. Design the contracts between production infrastructure and every tool that touches it. All other teams at Fluidstack use your tooling to manage and operate our hyperscale fleet.
• Build the production control plane. Unified machine management, actual state inspection, distributed command execution — and the Kubernetes-based infrastructure that underpins it all.
• Own fleet state as source of truth. SLOs, site lifecycle state, and integration with internal infrastructure management and customer-facing operations platforms. What the system says about itself should match reality, and you're accountable when it doesn't.
• Land new hardware into the platform cleanly. ZTP, DHCP, DNS, artifacts — every new XPU generation and site integration goes through IaaS before production.
Qualifications:
Required:
• You treat toil as a bug. If something requires a human to do it twice, you build the thing that makes it not require a human.
• You design APIs that age well. You've felt the pain of a leaky abstraction at scale and you don't repeat it.
• You move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else.
• You learn at a steep slope. You reach real competence in an unfamiliar domain fast. We value this over existing expertise.
• You carry a pager without flinching. You run the incident, write the postmortem, fix the systemic cause, and move on.
• You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day.
• You've shipped production services that other teams depend on at scale, and you're comfortable in any language using AI coding tools.
Preferred:
• Distributed systems and data pipeline engineering.
• Time-series observability stacks (Prometheus, Thanos, VictoriaMetrics).
• API design and versioning at scale.
• Workflow and orchestration engines (Temporal, Cadence).
• BMC/Redfish or hardware telemetry.
• Go, Python, and Postgres.
Company:
Fluidstack provides cloud infrastructure for AI with GPU clusters, orchestration, and monitoring for intensive workloads. Founded in 2017, the company is headquartered in New York, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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