# AI Inference Core - Software Integration Engineer

**Company:** [Cerebras Systems](https://hotfix.jobs/companies/cerebras-systems)
**Location:** Unspecified
**Role:** Fullstack Engineering
**Experience:** 0+ years
**Skills:** Python, C++, Go, Ai Frameworks, Distributed Systems, Compilers, Kernels, Runtimes, Hardware Accelerators, LLMs, Microservices, Containers, Kubernetes, Cloud Infrastructure, High-Performance Computing
**Posted:** 2026-02-05

> The Software Integration Engineer turns ambiguous inference ideas and prototypes into validated capabilities across AI frameworks, runtimes, compilers, kernels, distributed systems, and hardware. The role requires strong programming fundamentals, cross-component debugging, ownership, and comfort working on accelerated timelines.

## Job Description

## Responsibilities
- Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.
- Take high-value projects from zero to one, from incomplete ideas or prototypes to working, validated capabilities.
- 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 issues.
- Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.
- Work effectively on accelerated timelines while keeping technical risks, dependencies, and decisions visible.
- Manage changing priorities and drive ambiguous situations toward concrete outcomes.
- Identify bottlenecks, failure modes, edge cases, and integration gaps affecting inference correctness, performance, or delivery.
- Capture lessons from urgent work to improve automation, diagnostics, documentation, and repeatable practices.
- Help teammates move faster, make better decisions, and close difficult problems together.

## Requirements
- Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
- Ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
- Experience building or debugging software systems through professional work, internships, research, academic projects, open source, or equivalent hands-on work.
- 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 stay effective during uncertainty, rapid change, and accelerated delivery.
- Clear communication and strong collaboration across disciplines and experience levels.

## Preferred Skills
- Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
- Experience taking an ambiguous problem, early idea, or prototype from zero to a working and reliable capability.
- 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.
- Track record of driving cross-team projects from an incomplete idea to a reliable working result.

## Work Arrangement
- Hybrid schedule with in-office presence three days per week.
- Fully remote work is not available.
- Office locations: Sunnyvale, CA or Toronto, ON.

## Benefits
- Opportunity to build a breakthrough AI platform beyond the constraints of GPUs.
- Opportunities to publish and open source cutting-edge AI research.
- Work on a high-performance AI supercomputer.
- Startup vitality with job stability.
- Non-corporate work culture that respects individual beliefs.

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