Software Integration Engineer, AI Inference Core

Cerebras

. Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform .

Posted 11/6/2026full-timeSunnyvale • California • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong software engineering fundamentals with expertise in Python, C++, and Go, alongside experience in software/hardware co-design and debugging complex systems. Proven ability to drive cross-component projects from concept to validated capabilities while collaborating effectively across disciplines.

Highest-signal resume keywords

Software Engineering FundamentalsPython ProgrammingC++ ProgrammingAI Infrastructure ExperienceDebugging Complex Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonC++GoSoftware/Hardware Co-DesignDebuggingDistributed SystemsAI FrameworksModel DeploymentPerformance DebuggingLow-Level Systems

Soft Skills

Clear CommunicationStrong CollaborationProblem-SolvingAdaptabilityCuriosity

Tools & Technologies

MicroservicesContainersCluster OrchestrationCloud InfrastructureHigh-Performance Computing

Industry Keywords

AI WorkloadsLarge-Scale Compute ClustersFailure AnalysisIntegration GapsStartup Environment

Tech Stack

Tools & technologies

CloudDistributed SystemsMicroservicesOpen SourcePythonC++Go

About the role

Key responsibilities & impact

Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform
Take high-value projects from zero to one, from incomplete idea or prototype to 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 issues
Investigate and debug 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 affecting inference correctness, performance, or delivery
Capture lessons from urgent work to improve future integration speed and repeatability
Help teammates move faster, make better decisions, and close difficult problems together

Requirements

What you’ll need

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, open source, or equivalent hands-on work
Clear communication and strong collaboration across disciplines and levels of experience
Preferred: experience in a startup or similarly fast-moving, resource-constrained engineering environment
Preferred: experience taking a project from zero to one
Preferred: ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution
Preferred: curiosity about complex systems across component boundaries
Preferred: willingness to read unfamiliar code, learn new stack layers, and take ownership beyond a narrowly defined area
Preferred: ability to work hard during uncertainty, rapid change, and accelerated delivery
Preferred: track record of driving cross-team projects from incomplete idea to reliable working result
Must work in-office three days per week; fully remote work is unavailable
Must be willing to relocate to Toronto or Sunnyvale if not currently located there

Benefits

Comp & perks

Job stability with startup vitality
Continuous learning, growth and support
Opportunity to publish and open source cutting-edge AI research
Opportunity to work on one of the fastest AI supercomputers
Simple, non-corporate work culture
Equal and diverse work environment