Cerebras

1 day ago

AI Inference Core - Senior Technical Program Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 28 minutes agoStatus: Live

Job Summary

Lead an accountable operating layer for AI Inference Core, connecting feature development through release integration testing, release qualification, Core Infrastructure readiness, and branch stability. Define entry/exit criteria, owners, dependencies, SLAs, and health tracking for pre- and post-merge E2E stability. Coordinate cross-team roadmaps and risks while building dashboards, decision logs, and escalation follow-through that engineering trusts.

Location: Sunnyvale, Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Director level

Key Responsibilities

•Define how features move from development and feature qualification into release integration testing and release qualification, with owners, evidence, dependencies, and exception paths.
•Own pre-merge and post-merge E2E stability mechanisms: publish health, track SLA breaches, drive triage/escalation, document decisions, and close recurring-failure loops.
•Convert Inference Core priorities into goals, milestones, owners, risks, success measures, and review cadences with a dependable view of commitments.
•Coordinate planning and execution across release integration testing, Core Infrastructure, feature teams, release owners, and partner organizations; synchronize roadmaps, staffing, and cross-team dependencies.
•Build and maintain dashboards, SLA reporting, dependency maps, risk registers, decision logs, action tracking, and executive-ready status communication.

Key Requirements

•Significant experience leading complex technical programs across multiple engineering teams, ideally in infrastructure, distributed systems, platforms, release engineering, or AI systems.
•Strong technical fluency to understand architecture, system dependencies, quality evidence, operational risk, and engineering trade-offs.
•Proven ability to design and implement durable operating mechanisms (not just status reporting or scheduling meetings).
•Experience defining goals, milestones, ownership, entry and exit criteria, SLAs, risk management, and executive review cadences.
•Ability to influence technical leaders and teams without direct authority while preserving clear engineering ownership.

Experience:AI systemsDistributed systemsRelease engineeringInfrastructure

Skills:Analytical skillsCommunicationDecision-makingEscalationCross-team influence

Tech Stack:AI Inference CoreCore InfrastructureE2E testingCI/CDDashboardsSLA reportingDependency mapsRisk registersObservabilityIncident learning

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

1 day ago

AI Inference Core - Senior Technical Program Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 28 minutes agoStatus: Live

Job Summary

Location: Sunnyvale, Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: Program & Project Management (PMO)

Seniority: Director level

Key Responsibilities

•Define how features move from development and feature qualification into release integration testing and release qualification, with owners, evidence, dependencies, and exception paths.
•Own pre-merge and post-merge E2E stability mechanisms: publish health, track SLA breaches, drive triage/escalation, document decisions, and close recurring-failure loops.
•Convert Inference Core priorities into goals, milestones, owners, risks, success measures, and review cadences with a dependable view of commitments.
•Coordinate planning and execution across release integration testing, Core Infrastructure, feature teams, release owners, and partner organizations; synchronize roadmaps, staffing, and cross-team dependencies.
•Build and maintain dashboards, SLA reporting, dependency maps, risk registers, decision logs, action tracking, and executive-ready status communication.

Key Requirements

•Significant experience leading complex technical programs across multiple engineering teams, ideally in infrastructure, distributed systems, platforms, release engineering, or AI systems.
•Strong technical fluency to understand architecture, system dependencies, quality evidence, operational risk, and engineering trade-offs.
•Proven ability to design and implement durable operating mechanisms (not just status reporting or scheduling meetings).
•Experience defining goals, milestones, ownership, entry and exit criteria, SLAs, risk management, and executive review cadences.
•Ability to influence technical leaders and teams without direct authority while preserving clear engineering ownership.

Experience:AI systemsDistributed systemsRelease engineeringInfrastructure

Skills:Analytical skillsCommunicationDecision-makingEscalationCross-team influence

Tech Stack:AI Inference CoreCore InfrastructureE2E testingCI/CDDashboardsSLA reportingDependency mapsRisk registersObservabilityIncident learning

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn