AI Inference Core - SDET Technical Lead, Release Integration Testing

Responsibilities

• Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
• 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 end-to-end validation across the cloud-to-wafer stack and add risk-based scenarios to release regression.
• Improve master and release-branch stability through health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines.
• Lead first-pass regression and rollout triage, coordinate resolution owners, drive root-cause analysis, 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.

Requirements

• Strong software-engineering fundamentals and programming ability in Python, Go, or a similar language.
• Technical leadership experience 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.
• 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.

Preferred Skills

• Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.
• Experience with AI infrastructure, model deployment, LLMs, multimodal workloads, or large-scale compute clusters.
• Experience building test frameworks, distributed test systems, release pipelines, dashboards, or internal developer tooling.
• Experience with performance testing, profiling, observability, fault injection, reliability, or production failure analysis.
• Experience in a startup or similarly fast-moving engineering environment.
• Track record of taking a quality or release capability from zero to one and scaling it across teams.
• Familiarity with containers, cluster orchestration, cloud infrastructure, CI/CD, or high-performance computing.

Benefits

• Build a breakthrough AI platform beyond the constraints of GPUs.
• Publish and open source cutting-edge AI research.
• Work on a fast AI supercomputer.
• Job stability with startup vitality.
• A non-corporate work culture that respects individual beliefs.

Work Arrangement

• In-office presence at least three days per week; fully remote work is not available.