Project Manager, IT Project Manager

Overview

Job title:

Program, Project Manager - Technical Program Manager

Work on NVIDIA Metropolis platform offering GPU-accelerated libraries, SDKs, microservices, tools, and blueprints.

Enable development, deployment, and scaling of AI-enabled applications from edge to cloud. Lead full lifecycle concept, model training, optimized inference, and deployment.

• Work Location (Tax):
  Santa Clara, California, USA
• Start Date:
  
  June 1, 2026
• End Date:
  November 30, 2026

• Work closely with engineering and product management to drive strategic roadmap execution.
• Collaborate in Agile ceremonies sprint planning, stand-ups, reviews, and retrospectives.
• Use Jira dashboards and bug databases for reporting;
  Confluence for program updates.
• Track KPIs with engineering teams to improve execution and deliverables.
• Act as integral member of Vision AI development and productization workflows.
• Facilitate communication between stakeholders and leadership to align goals and resolve dependencies.

• Education
  :
  Bachelor`s degree in Electrical Engineering or Computer Science or equivalent experience.
• Experience
  : 6+ years of end-to-end Program Management experience; experience in similar or related roles.
• Core Skills
  :
  Excellent verbal, written, interpersonal, and presentation skills;
  Proficiency in Agile methodologies;
  Strong experience with Atlassian tools (Jira, Confluence) and ability to guide teams;
  Highly organized, detail-oriented, strong listening skills;
  Ability to work in fast-paced, high-uncertainty environments and adapt quickly;
  Strong prioritization and alignment-building skills;
  Ability to think long-term and build consensus.

• Experience in Vision AI or AI application development lifecycle (data acquisition, labeling, training, optimization, deployment).
• Understanding of Embedded Systems (NVIDIA GPU familiarity is a plus).
• Deep understanding of Software Product Lifecycle for production-grade AI.
• Use of AI in Program Management to improve workflows and team velocity.
• Experience managing AI-specific challenges like model accuracy KPIs and human-in-the-loop validation.