H-1B Visa Distributed Systems Engineer Jobs
Distributed Systems Engineer roles sit squarely within H-1B visa specialty occupation criteria, requiring at least a bachelor's degree in computer science, software engineering, or a directly related field. Large tech employers, cloud infrastructure companies, and fintech firms file LCAs for this role regularly, making it one of the more sponsor-accessible titles in the H-1B market.
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Involves a hybrid of multiple computational / data / Cyberinfrastructure (CI) dominated fields such as, but not limited to, bioinformatics, geological information services (GIS), data analytics, and computational chemistry. Applies computational, computer science, data science and cyber infrastructure (CI) research and development principles, with relevant domain science knowledge, to perform research and technology integration and development. Responsibilities include research, design, development, analysis, operation, and support of high performance computing (HPC) and data science research, software, tools and hardware resources. Develops data algorithms and performs computations, statistical analyses, interpretation and reporting of research. This specialty / function exists for those positions whose primary responsibility is to do research and use computational and data science technology as a tool to accomplish the research.
The Preclinical Design and Clinical Translation of Regimens for Tuberculosis (PReDiCTR-TB) Consortium is a 21st-century, model-informed drug development (MIDD) platform integrating computational science, translational pharmacology, and global clinical insight to accelerate the design and delivery of transformative TB regimens.
Positioned at the intersection of data, biology, engineering, econometrics, and decision science, PReDiCTR-TB functions as a strategic intelligence engine for regimen development, linking preclinical evidence, synthetic experiments, mechanistic models, and clinical data into a unified predictive framework. By embedding quantitative systems pharmacology (QSP), AI-driven analytics, and probabilistic decision modeling throughout development, the consortium enables real-time prioritization of regimens with the highest probability of clinical success.
Rather than advancing compounds in isolation, PReDiCTR-TB takes a regimen-first, translation-driven approach that optimizes combinations, dosing strategies, and treatment durations through iterative simulation-validation cycles grounded in human-relevant biology. This framework helps reduce reliance on costly empirical experimentation while increasing translational fidelity from bench to bedside.
The consortium delivers:
- Predictive insights that de-risk development earlier
- Optimized trial designs informed by mechanistic and statistical rigor
- Faster and more confident go/no-go decisions across the R&D lifecycle
PReDiCTR-TB is redefining how infectious disease regimens are designed, prioritized, and translated into clinical impact.
Custom Scope
Model-informed drug development (MIDD) and AI in Clinical Trials market is experiencing a massive shift, projected to skyrocket from $1.35 billion to $2.74 billion by 2030. Data and model-driven efficiencies in patient selection, drug repurposing, and real-time trial monitoring are fundamentally compressing drug development timelines.
At the UCSF Savic Lab, we aren't just reacting to this shift—we are driving it. We are moving past traditional, isolated data storage models to establish a modern, highly interconnected, and secure data & model infrastructure.
We are seeking a solution-minded, highly technical, and mission-driven Distributed Data Pipeline Architect. In this role, you will design, build, lead implementation, and operate a research-grade, scale-distributed data architecture. This framework will serve as the foundation for advanced analytics, multi-institution translational science, and 21st-century accelerated drug development decision support.
Department Overview
The Savic Lab is a global leader in model-informed drug development for infectious diseases and serves as a quantitative innovation hub for translational pharmacology, AI-enabled modeling, and next-generation regimen design. The laboratory conducts groundbreaking research across TB, HIV, malaria, pediatric infectious diseases, translational PK/PD, and systems pharmacology. Through its leadership role in PReDiCTR-TB, the lab collaborates with international partners to integrate computational science, mechanistic modeling, and clinical translation into actionable strategies that improve global health outcomes.
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion.
REQUIRED QUALIFICATIONS
- Experience: 5+ years of hands-on experience in data engineering, distributed systems, or enterprise platform architecture.
- Systems Design: A proven track record of architecting, deploying, and maintaining production-grade distributed data architectures.
- Data Processing: Direct experience handling large-scale data ingestion, multi-tenant databases, and event-driven data flows.
- Communication: Exceptional communication and presentation skills, with a demonstrated ability to explain complex technical concepts to non-technical executive stakeholders.
- Bachelor's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience.
PREFERRED QUALIFICATIONS
- Architectures: Data mesh environments, data fabric layers, and semantic web modeling.
- Streaming & Compute: Apache Kafka, Pulsar, AWS Kinesis, Apache Spark, Flink, or Apache Beam.
- Storage & Databases: Distributed object storage (S3-compatible API environments) and NoSQL systems (Cassandra, DynamoDB, MongoDB).
- Clinical Data Standards: Familiarity with NIH-preferred schemas and ontologies (e.g., BIDS for imaging, OMOP common data models, LOINC, SNOMED CT, or FHIR transfer protocols).
- Governance & Security: Data cataloging, automated data lineage tools, and strict data access control frameworks (HIPAA / NIST compliance).
- Master's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization preferred.
INTRODUCTION
Involves a hybrid of multiple computational / data / Cyberinfrastructure (CI) dominated fields such as, but not limited to, bioinformatics, geological information services (GIS), data analytics, and computational chemistry. Applies computational, computer science, data science and cyber infrastructure (CI) research and development principles, with relevant domain science knowledge, to perform research and technology integration and development. Responsibilities include research, design, development, analysis, operation, and support of high performance computing (HPC) and data science research, software, tools and hardware resources. Develops data algorithms and performs computations, statistical analyses, interpretation and reporting of research. This specialty / function exists for those positions whose primary responsibility is to do research and use computational and data science technology as a tool to accomplish the research.
The Preclinical Design and Clinical Translation of Regimens for Tuberculosis (PReDiCTR-TB) Consortium is a 21st-century, model-informed drug development (MIDD) platform integrating computational science, translational pharmacology, and global clinical insight to accelerate the design and delivery of transformative TB regimens.
Positioned at the intersection of data, biology, engineering, econometrics, and decision science, PReDiCTR-TB functions as a strategic intelligence engine for regimen development, linking preclinical evidence, synthetic experiments, mechanistic models, and clinical data into a unified predictive framework. By embedding quantitative systems pharmacology (QSP), AI-driven analytics, and probabilistic decision modeling throughout development, the consortium enables real-time prioritization of regimens with the highest probability of clinical success.
Rather than advancing compounds in isolation, PReDiCTR-TB takes a regimen-first, translation-driven approach that optimizes combinations, dosing strategies, and treatment durations through iterative simulation-validation cycles grounded in human-relevant biology. This framework helps reduce reliance on costly empirical experimentation while increasing translational fidelity from bench to bedside.
The consortium delivers:
- Predictive insights that de-risk development earlier
- Optimized trial designs informed by mechanistic and statistical rigor
- Faster and more confident go/no-go decisions across the R&D lifecycle
PReDiCTR-TB is redefining how infectious disease regimens are designed, prioritized, and translated into clinical impact.
Custom Scope
Model-informed drug development (MIDD) and AI in Clinical Trials market is experiencing a massive shift, projected to skyrocket from $1.35 billion to $2.74 billion by 2030. Data and model-driven efficiencies in patient selection, drug repurposing, and real-time trial monitoring are fundamentally compressing drug development timelines.
At the UCSF Savic Lab, we aren't just reacting to this shift—we are driving it. We are moving past traditional, isolated data storage models to establish a modern, highly interconnected, and secure data & model infrastructure.
We are seeking a solution-minded, highly technical, and mission-driven Distributed Data Pipeline Architect. In this role, you will design, build, lead implementation, and operate a research-grade, scale-distributed data architecture. This framework will serve as the foundation for advanced analytics, multi-institution translational science, and 21st-century accelerated drug development decision support.
Department Overview
The Savic Lab is a global leader in model-informed drug development for infectious diseases and serves as a quantitative innovation hub for translational pharmacology, AI-enabled modeling, and next-generation regimen design. The laboratory conducts groundbreaking research across TB, HIV, malaria, pediatric infectious diseases, translational PK/PD, and systems pharmacology. Through its leadership role in PReDiCTR-TB, the lab collaborates with international partners to integrate computational science, mechanistic modeling, and clinical translation into actionable strategies that improve global health outcomes.
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion.
REQUIRED QUALIFICATIONS
- Experience: 5+ years of hands-on experience in data engineering, distributed systems, or enterprise platform architecture.
- Systems Design: A proven track record of architecting, deploying, and maintaining production-grade distributed data architectures.
- Data Processing: Direct experience handling large-scale data ingestion, multi-tenant databases, and event-driven data flows.
- Communication: Exceptional communication and presentation skills, with a demonstrated ability to explain complex technical concepts to non-technical executive stakeholders.
- Bachelor's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience.
PREFERRED QUALIFICATIONS
- Architectures: Data mesh environments, data fabric layers, and semantic web modeling.
- Streaming & Compute: Apache Kafka, Pulsar, AWS Kinesis, Apache Spark, Flink, or Apache Beam.
- Storage & Databases: Distributed object storage (S3-compatible API environments) and NoSQL systems (Cassandra, DynamoDB, MongoDB).
- Clinical Data Standards: Familiarity with NIH-preferred schemas and ontologies (e.g., BIDS for imaging, OMOP common data models, LOINC, SNOMED CT, or FHIR transfer protocols).
- Governance & Security: Data cataloging, automated data lineage tools, and strict data access control frameworks (HIPAA / NIST compliance).
- Master's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization preferred.
See all 45+ H-1B Visa Distributed Systems Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Distributed Systems Engineer
Align your degree to the role
USCIS evaluates whether your specific degree field directly supports the job duties. A computer science or software engineering degree maps cleanly, but an unrelated STEM degree may require a credential evaluation letter explaining the connection to distributed systems work.
Filter employers by LCA filing history
Use Migrate Mate to search verified DOL Labor Condition Application filings for Distributed Systems Engineer roles. This shows you which companies have already completed the employer-side compliance step, not just which ones claim to sponsor.
Target E-Verify enrolled employers early
STEM OPT extensions and H-1B cap-gap status both require your employer to be enrolled in E-Verify. Confirm enrollment before accepting an offer to avoid authorization gaps during the transition from OPT to H-1B status.
Benchmark your wage against the prevailing rate
Run your target job title and metro area through the OFLC Wage Search before negotiating. Your offered salary must meet the DOL prevailing wage for the role's SOC code, and distributed systems positions often map to higher wage levels in major tech markets.
Get your credentials evaluated before interviewing
If your degree is from outside the U.S., a NACES-member credential evaluation documenting U.S. equivalency speeds up the LCA and I-129 stages. Employers filing H-1B petitions need this before USCIS can confirm specialty occupation eligibility.
Clarify petition timing during the offer stage
H-1B cap filings open in March for an October 1 start. If you're interviewing in summer or fall, ask whether the employer will file in the next registration window or hold the role. Cap-exempt employers at universities or nonprofit research labs can file any time.
H-1B Visa Distributed Systems Engineer: Frequently Asked Questions
Does a Distributed Systems Engineer role qualify for H-1B sponsorship?
Yes. Distributed systems engineering meets the H-1B specialty occupation definition because the role typically requires at least a bachelor's degree in computer science, software engineering, or a closely related field. The O*NET profile for software developers and systems engineers supports this classification. Employers confirm the requirement through the LCA filing, which documents the job duties and minimum degree requirement.
Which types of employers sponsor H-1B visas for this role?
Cloud infrastructure companies, large-scale tech platforms, financial technology firms, and enterprise software companies are frequent sponsors for distributed systems roles. Cap-exempt employers, including research universities and affiliated nonprofits, can file H-1B petitions outside the annual lottery window. Browse Migrate Mate to see which companies have active LCA filings for this specific job title.
How does the H-1B lottery affect my job search as a distributed systems engineer?
Cap-subject H-1B petitions are subject to an annual lottery with registration in March and an October 1 start date. If you're on OPT when you're selected, cap-gap rules extend your work authorization through September 30. Cap-exempt employers at qualifying research institutions and nonprofits aren't subject to the lottery, so targeting those organizations can eliminate timing uncertainty.
What does the LCA process mean for distributed systems roles specifically?
Your employer files a Labor Condition Application with the DOL before submitting your H-1B petition to USCIS. For distributed systems engineers, the LCA certifies that your offered wage meets or exceeds the prevailing wage for the role's SOC code in your work location. Roles in high-cost metros like San Francisco or Seattle typically fall under higher DOL wage levels, which the employer must commit to in writing.
Can I switch employers after my H-1B is approved for a distributed systems role?
Yes, H-1B portability under AC21 lets you change employers while a new I-129 petition is pending, as long as you've had H-1B status for at least 180 days and the new role is in the same or a similar occupational classification. Distributed systems roles generally port well across tech employers because the SOC code and specialty occupation basis remain consistent. USCIS reviews the new petition independently.