AI Inference Core - Software Integration Engineer

Job Title

AI Inference Core - Software Integration Engineer

Role Summary

Join the AI Inference Core team to integrate, validate, and deliver cross-component inference capabilities across AI frameworks, runtimes, compilers, kernels, distributed systems, and hardware. The role focuses on turning ambiguous ideas and prototypes into reliable, release-ready features.

Experience Level

Mid-level. The role welcomes engineers from strong junior contributors to experienced practitioners; no explicit years-of-experience requirement was specified.

Responsibilities

Primary responsibilities include cross-stack integration, debugging, and driving projects from prototype to validated delivery.

• Integrate and validate software components across AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
• Take high-value projects from zero to one: convert incomplete ideas or prototypes into working, validated capabilities.
• Drive cross-component projects from problem definition through integration, validation, and release readiness.
• Investigate and debug difficult failures spanning large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.
• Collaborate with software and hardware engineers to make co-design trade-offs and resolve system-level issues.
• Work on accelerated timelines, manage rapidly changing priorities, and keep risks and dependencies visible.
• Identify bottlenecks, failure modes, edge cases, and integration gaps affecting correctness or performance.
• Capture lessons from urgent work to improve automation, diagnostics, documentation, and repeatability.
• Mentor and enable teammates to move faster and close difficult cross-team problems.

Requirements

Must-have technical skills, problem-solving ability, and collaboration traits for day-to-day work.

• Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
• Proven ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
• Hands-on experience building or debugging software systems (professional work, open source, or equivalent practical experience).
• Curiosity about system behavior across component boundaries and willingness to read unfamiliar code and learn new stack layers.
• Ability to work effectively under uncertainty, rapid change, and accelerated delivery schedules.
• Clear communication and strong cross-discipline collaboration skills.

Nice-to-have:

• Experience in startup or fast-moving engineering environments and taking projects from zero to one.
• Background in software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
• Experience debugging distributed systems, large compute clusters, or performance/profiling/observability tooling.
• Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.
• Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.

Education Requirements

No specific degree is required. Candidates may qualify via professional experience, internships, research, academic projects, open source contributions, or equivalent hands-on experience.

About the Company

Company: Cerebras

Headquarters: Sunnyvale, CA, USA

Developer of wafer-scale AI accelerators, Cerebras designs the Wafer Scale Engine (WSE)—one of the world’s largest AI chips—to deliver high-speed training and inference solutions for model labs, enterprises, and AI-native startups.