Release Qualification Team Lead

The role

The Release Qualification Team Lead will own weekly end-to-end release qualification for Cerebras Cloud, Inference Platform, and Inference API. You will build and run a purpose-built team to triage, debug, and decide on release blockers.

What you will do

• Drive weekly end-to-end release qualification as the accountable owner.
• Build and run a purpose-built release qualification team.
• Own the full release qualification lifecycle including test planning, release planning, and documentation.
• Own triage, debug, and escalation during release windows.
• Drive expanded end-to-end coverage across Cloud, Inference Platform, and Inference API.
• Partner with the cross-org release qualification team as the technical counterpart.
• Distinguish real regressions from flakiness and maintain a record of escalations.
• Mentor engineers on triage, debugging practices, and qualification methodology.

Required qualifications

• 7+ years of relevant industry experience in software integration, development, or quality engineering, including prior release qualification experience.
• Proven ownership of end-to-end release or qualification processes for complex, distributed systems.
• Strong track record of debugging complex issues across distributed, scaled-out deployments under release-blocking time pressure.
• Deep expertise in automation and programming using one or more languages such as Python.
• Ability to build reusable test frameworks from the ground up.
• Demonstrated ability to lead cross-functional initiatives spanning multiple orgs, product development, product management, and field teams.
• Sound judgment on coverage trade-offs, risk-based prioritization, and go/no-go release decisions.
• Excellent verbal and written communication skills.
• Experience presenting technical findings to both engineering and leadership audiences.
• Strong organizational skills and ownership mindset.
• Experience leading and mentoring engineers across geographically dispersed teams and time zones.

Nice to have

• Hands-on experience with ML workloads including LLM and/or multimodal training or inference.
• Experience designing test strategies for distributed systems, cloud infrastructure, and microservices.
• Experience with microservices deployment, debugging, and orchestration at scale.
• Familiarity with hardware-backed inference services and the trade-offs of hardware/software.
• Prior experience building or significantly shaping a team's quality engineering culture or test infrastructure.

Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source cutting-edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Job stability with startup vitality.
• Simple, non-corporate work culture that respects individual beliefs.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.