Developer Experience Software / Systems Reliability Engineer

NUVACORE; Santa Clara (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

NUVACORE is building a ground-up, high-performance, low-power CPU for next-generation AI compute workloads. We seek a Software or Systems Reliability Engineer to own front-end tool flows used by design and verification teams to develop and verify the CPU.

You will collaborate with hardware engineers on build/test workflows, provide reliability metrics, and drive scalable, reproducible flows from RTL to test benches.

Qualifications

• BS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• Experience designing and implementing complex build systems with hierarchical dependencies.
• Hands-on experience with Bazel and/or Buck, writing rules/macros.
• Experience designing CI systems with dependency-aware build/test selection.
• Experience with job scheduling for long-running workloads (Slurm, LSF, Kubernetes).
• Experience with distributed storage systems and caching strategies.
• Strong software engineering in Python, Rust, Go, or shell; infrastructure as code.
• Solid understanding of Linux operating system administration.

Responsibilities

• Build System Architecture: design and own build system; manage rules, dependencies, remote execution, caching.
• Continuous Integration: design pipelines to gate design changes and minimize test scope.
• Job Scheduling & Orchestration: model and schedule long-running, resource-heavy jobs across the compute farm.
• Distributed Storage & Data Management: store, cache, version, and expire build artifacts and data.
• Reliability & Observability: instrument flows with metrics, logs, traces; track SLOs and root-cause issues.
• Flow Integration: wrap vendor tools as hermetic build actions; collaborate with design/verification teams.

Skills

Build system design

Dependency graphs

Python

Rust

Go

Shell scripting

Linux administration

CI/CD

Job scheduling

Education

BS in CS/CE/EE

Tools

Buck

Bazel

Buck2

Kubernetes

Slurm

LSF

Nextflow

Job description

Nuvacore is building a ground-up, high-performance, low-power CPU for next-generation agentic AI compute workloads. We are seeking a Software or Systems Reliability Engineer with a strong background in developer tools/experience to build and own the front-end tool flows that our design and verification teams rely on to develop and verify the CPU. You will work closely with hardware design and verification engineers to keep build and test workflows (simulation, emulation, synthesis, lint, CDC, and formal verification) fast, reliable, scalable, and delightful.

THE ROLE

• Build System Architecture: Design and own the build system that turns a large, hierarchical RTL and verification codebase into reproducible, incremental, cacheable builds. We use Buck2; you'll own the rule set, the dependency model, and the remote-execution and caching strategy as the design grows.
• Continuous Integration: Design the pipelines that gate design changes, with a particular focus on build and test selection, so each change runs the smallest set of long-running tests that can catch its regressions.
• Job Scheduling & Orchestration: Model and schedule heterogeneous, long-running, resource-constrained jobs (hours-long, memory-heavy, license-gated) across the compute farm, and build the orchestration layer that sequences multi-stage workflows and surfaces their results.
• Distributed Storage & Data Management: Decide how build artifacts, test outputs, and design data are stored, cached, versioned, and expired across distributed storage, including content-addressed caches, retention policies, and data locality on the farm.
• Reliability & Observability: Instrument the flows with metrics, logs, and traces; define and track SLOs for turnaround time, flakiness, and failure attribution; drive root-cause fixes rather than reruns.
• Flow Integration: Wrap vendor tools as hermetic build actions with explicit inputs and outputs. Partner with design and verification engineers to understand their workflows.

Requirements — Must Have

• BS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• Experience designing and implementing complex build systems with hierarchical dependencies: dependency graphs, incrementality, hermeticity, and caching.
• Hands-on experience with Bazel and/or Buck, specifically writing rules and macros.
• Experience designing continuous integration systems, especially dependency-aware build and test selection.
• Experience with job scheduling for long-running, resource-constrained workloads (Slurm, LSF, Kubernetes, or similar).
• Experience with distributed storage systems and the tradeoffs they impose on consistency, locality, caching, and retention.
• Strong software engineering in Python, Rust, Go, and/or shell: tested, reviewed, maintainable code, with infrastructure treated as software.
• Solid understanding of Linux operation system administration.

Requirements — Nice To Have

• Experience in a semiconductor or hardware design environment, building or supporting front-end EDA flows (RTL simulation, emulation, lint/CDC, synthesis, or formal).
• Hands-on experience with EDA verification tools such as Synopsys VCS, Cadence Xcelium, and/or Jasper formal verification tools.
• Hands-on experience with EDA emulation platforms (Synopsys Zebu, Cadence Palladium)
• Working knowledge of RTL design and verification flows, enough to debug flow issues alongside design and verification engineers.
• Experience with remote execution and remote caching (Buck2 RE, Bazel RBE, BuildBarn, BuildBuddy, NativeLink, or similar).
• Experience with workflow orchestration engines (Nextflow, Snakemake, Airflow, Temporal, or similar).
• Exposure to cloud compute for large engineering workloads (AWS, Azure, or GCP).
• Familiarity with EDA tool licensing models and how they constrain scheduling (FlexLM/FlexNet).

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.