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Distributed Systems Software Engineer Jobs (NOW HIRING)

Meta

Software Systems Engineer

Austin, TX

$144K/yr

Meta is seeking a Software Systems Engineer to join our Production Systems Engineering organization ... Experience designing and operating distributed systems software at scale, including monitoring ...

Meta

Software Systems Engineer

Bellevue, WA

$144K/yr

Meta is seeking a Software Systems Engineer to join our Production Systems Engineering organization ... Experience designing and operating distributed systems software at scale, including monitoring ...

Meta

Software Systems Engineer

Fremont, CA

$144K/yr

Meta is seeking a Software Systems Engineer to join our Production Systems Engineering organization ... Experience designing and operating distributed systems software at scale, including monitoring ...

4pconsultinginc

Software Engineer IV

Birmingham, AL · On-site

$114K - $151K/yr

This role requires strong experience in large-scale distributed systems, object-oriented ... Software Engineering & Architecture * Design, develop, test, and modify sophisticated software ...

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Distributed Systems Software Engineer information

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$83K

$177.7K

$206K

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

As of Jul 23, 2026, the average yearly pay for distributed systems software engineer in the United States is $177,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $173,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Distributed Systems Software Engineer, and why are they important?

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 are Distributed Systems Software Engineers?

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.
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What job categories do people searching Distributed Systems Software Engineer jobs look for? The top searched job categories for Distributed Systems Software Engineer jobs are:
Distributed Systems Software Engineer jobs near you
Infographic showing various Distributed Systems Software Engineer job openings in the United States as of July 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $177,719 per year, or $85.4 per hour.

Software Engineer, Distributed Systems (Core)

Career Renew

Los Angeles, CA • Remote

$180K - $320K/yr

Full-time

Posted 8 hours ago

Job description

Career Renew is recruiting for one of its clients a Software Engineer, Distributed Systems (Core) - this is a fully remote role for US/Canada candidates. Salary range: 180-320K USD yearly plus benefits plus equity. Visa sponsorship available.

Our mission is to empower everyone to take action on their data. Hundreds of companies, including Autotrader, Calendly, Cars.com, Monday.com, and PetSmart, trust us to power their growth.


We pioneered the Composable Customer Data Platform (CDP), which lets companies use their own data warehouse to collect, prepare, and activate customer data for marketing personalization and business operations. Our new AI Decisioning platform goes a step further, allowing marketers to set goals and guardrails that AI agents can then use to personalize 1:1 customer interactions. Traditionally, only technical teams had the skills to access and use customer data. With us, every business user can deliver personalized customer experiences, optimize performance marketing, and move faster by leveraging data and AI across their organization.

We are looking for a distributed systems engineer to work on the systems that power the syncing engine our customers and other engineering teams rely on. This presents an exciting challenge where you can apply your expertise in distributed systems, performance optimization, and troubleshooting to push the boundaries of what is possible and meaningfully improve our ability to move massive amounts of customer data. This role also provides a unique opportunity to work on a multi-cloud and multi-region infrastructure that supports a global customer base.


We believe in enabling our engineers to do their best work for our customers by giving them extremely high levels of ownership and autonomy. This comes in different forms: you will own and deliver projects from start to finish, you will work directly with customers to solve their hardest scaling problems, and you will have a lot of influence over what we work on as a team and company.


Some of the problems we’ll be working on include:

  • Sync Speed: Customers want to sync a lot of data to important destinations like Facebook and Snapchat, which requires us to analyze every part of our syncing process and find where we can optimize to sync data more quickly

  • Streaming Syncing: We currently sync data from sources in batch only, but envision a world where we also do syncs in real-time and support streaming sources like webhooks and queues

  • Scalability and Reliability: As part of our rapid growth, we’re always evaluating current future bottlenecks in scaling and reliability, and architecting for the next order of magnitude of growth

  • Personalization API: Our Personalization API product provides a low latency caching layer on top of data warehouses that enable customers to use their data warehouse for real-time personalization use cases with <30ms p90 response times with QPS in the millions

  • Multi-Region and Multi-Cloud: Supporting our multi-region and multi-cloud backend, including extending it to launch our platform in new regions to support data residency requirements of our global customer base

Requirements:
7+ years of experience as a software engineer with a very high level of general aptitude and work in distributed systems (Mandatory)
Have been part of high velocity startup through high stages of growth, Series B - Series E (i.e Stripe, Kong, Semgrep) (Mandatory)
Staff level minimum with a history of getting promoted quickly at the listed companies. (Mandatory)
Have graduated from a top 30 CS program such as: University of Waterloo, Harvard, Columbia, Princeton, Stanford, UC Berkeley, MIT, CMU, CalTech, Cornell, Duke, Dartmouth, Brown, IITs (Mandatory)
Extremely strong in systems design fundamentals and understanding of how large scale distributed systems behave (Mandatory)
You’ve created event collection or data streaming services that power company critical systems ( work with message queues, Kafka, SQL databases, Kubernetes, Docker) (Mandatory)
You’ve owned systems that have undergone orders of magnitude of growth and helped them scale accordingly (Mandatory)
You’ve built data sync engines that process and move terabytes of data per day in a scalable way (Nice-to-have)
Work close to the infrastructure layer of code, someone who knows how even the tools (i.e. spark, flink, kafka) are built (Nice-to-have)
Extremely strong communication skills, and are a fast learner who is excited to take on the challenges we face (Mandatory)