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AI Inference Core - Technical Lead Manager, Release Qual & Integration

Cerebras· Software Engineering
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Hybrid (Sunnyvale, CA), Hybrid (Toronto, CAN)Full-timePosted 2mo ago

About the role

Technical Lead Manager responsible for Release Integration Testing within AI Inference Core, defining quality strategy across pre-release and release cycles, leading cross-stack integration efforts, and mentoring engineers.

Responsibilities

  • Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
  • Engage early on high-risk inference changes; identify dependencies and interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.
  • Own the inference-path readiness gate by reviewing unit, simulation, benchmark, feature-test, and integration evidence, documenting gaps, and approving integration readiness before release entry.
  • Lead integrated inference E2E validation across features and the cloud-to-wafer stack; promote durable feature tests and add risk-based scenarios to release regression.
  • Improve master and release-branch stability through actionable health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines.
  • Lead first-pass regression and rollout triage, coordinate owners through resolution, drive RCA, place missing coverage at the correct layer, and plan rollout across multiple product and release projects.
  • Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; advance automation efficiency, diagnostics, probes, and roadmap test planning between active engagements.

Qualifications

  • Strong software-engineering fundamentals and programming ability in Python Go, or a similar language.
  • Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.
  • Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.
  • Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.
  • Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.
  • Ability to influence and align multiple engineering teams without relying solely on organizational authority.
  • Clear communication and sound judgment during high-pressure release situations, including the ability to explain technical risk to engineering and leadership audiences.

Skills

Required:Software engineeringTechnical leadershipAutomation/test architectureCross-stack debugging
Last updated Oct 25, 2026. Interested? Apply on the company site.

About Cerebras

Cerebras is the go-to platform for fast and effortless AI training. Learn more at cerebras.ai.

Cerebras is the go-to platform for fast and effortless AI training.

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