Software Integration Engineer

About The Role

Cerebras is seeking a Software Integration Engineer to join the AI Inference Core team. This team operates at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design. The role focuses on transforming ambitious ideas into working realities across the Cerebras inference stack, integrating and validating complex, cross-component projects under accelerated timelines.

A Special Task Force, Not a Typical Engineering Role

• Zero-to-one mission: Take incomplete ideas and early prototypes to fully working, validated capabilities.
• Cross-stack complexity: Work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware.
• Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work.
• Comfortable on the hot seat: Take ownership with unclear paths, make sound decisions with incomplete information, and remain effective under tight timelines.
• Bias for action: Cut through unnecessary ceremony to deliver results and subsequently build automation, diagnostics, documentation, and repeatable practices based on learnings.
• Team multiplier: Push work forward while enhancing the pace, clarity, and effectiveness of teammates.

What You Will Do

• Translate new inference ideas and features into integrated, working capabilities on the Cerebras platform.
• Develop high-value projects from initial concept or prototype to a working, validated capability.
• Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
• Drive complex, cross-component projects from problem definition through integration, validation, and release readiness.
• Collaborate with software and hardware engineers on co-design trade-offs and system-level issue resolution.
• Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware.
• Work effectively on accelerated timelines, maintaining visibility of technical risks, dependencies, and decisions.
• Participate in focused daily syncs, manage rapidly changing priorities, and drive ambiguous situations toward concrete outcomes.
• Identify bottlenecks, failure modes, edge cases, and integration gaps impacting inference correctness, performance, or delivery.
• Capture essential lessons from urgent work to improve future integration speed and efficiency.
• Foster momentum beyond personal work by enabling teammates to move faster, make better decisions, and collectively resolve difficult problems.

Requirements & Tech Stack

• Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
• Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
• Experience debugging complex systems, distributed software environments, or large-scale compute clusters.
• Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.
• Exposure to performance debugging, profiling, observability, or failure analysis.
• Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.
• Hands-on experience building or debugging software systems through professional work, internships, research, academic projects, or open source.
• Clear communication and strong collaboration skills across disciplines and experience levels.

Preferred Qualifications

• Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
• Demonstrated experience taking a project from zero to one: transforming an ambiguous problem, early idea, or prototype into a working and reliable capability.
• Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
• Curiosity about complex system behavior across component boundaries.
• Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined area.
• Ability to work hard and remain effective during periods of uncertainty, rapid change, and accelerated delivery.
• Track record of driving cross-team projects from an incomplete idea to a reliable working result.

Location

• Hybrid schedule with three days per week in-office presence.
• Office locations: Sunnyvale, CA or Toronto, ON.