AI Inference Core - Software Integration Engineer

The role

You will integrate and validate cross-component projects across the Cerebras inference stack. This involves turning incomplete ideas and prototypes into working capabilities across AI frameworks, runtimes, compilers, kernels, and hardware.

What you will do

• Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.
• Take high-value projects from zero to one.
• Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
• Drive cross-component projects from problem definition through integration, validation, and release readiness.
• Collaborate with software and hardware engineers to make co-design trade-offs and resolve system-level issues.
• Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.
• Work on accelerated timelines while keeping technical risks, dependencies, and decisions visible.
• Participate in focused daily syncs and manage rapidly changing priorities.
• Identify bottlenecks, failure modes, edge cases, and integration gaps.
• Capture lessons from urgent work to improve future integration.

Required qualifications

• 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.
• Experience building or debugging software systems through professional work, internships, research, academic projects, or open source.
• Clear communication and strong collaboration across disciplines.

Nice to have

• Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
• Demonstrated experience taking a project from zero to one.
• Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
• Curiosity about how complex systems behave 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 stay 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.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.