About the role

Senior Technical Program Manager responsible for overseeing engineering initiatives and process design for AI Inference Core at Cerebras. Focused on cross-team coordination and technical execution without direct authority.

Responsibilities

Define how features move from development and feature qualification into release integration testing and release qualification, including owners, entry and exit criteria, required evidence, dependencies, and exception paths.
Own the operating mechanism for pre-merge and post-merge E2E stability: publish health, track SLA breaches, drive triage and escalation, document decisions, and close recurring-failure loops.
Convert Inference Core priorities into clear goals, milestones, owners, risks, success measures, and review cadences while maintaining one 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.
Drive timely decisions and follow-through on blocked or slipping work, surfacing trade-offs and escalating when teams cannot resolve issues at the working level.
Continuously improve the operating model using delivery data, retrospectives, recurring-failure patterns, stakeholder feedback, and changes in business priorities.

Significant experience leading complex technical programs across multiple engineering teams, ideally in infrastructure, distributed systems, platforms, release engineering, or AI systems.
Strong technical fluency and the ability to understand architecture, system dependencies, quality evidence, operational risk, and engineering trade-offs.
Proven ability to design and implement durable operating mechanisms, not merely report status or schedule 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.
Strong analytical skills and experience using metrics, dashboards, and qualitative evidence to improve execution and decision quality.
Exceptional written and verbal communication, including concise executive synthesis and clear escalation under ambiguity or pressure.