Technical Program Manager II

What the role needs

• Technical Project Manager II
• Location: 3 days onsite in Menlo Park, CA or San Francisco, CA
• Duration: 12-month contract with possibility for extension
• Pay Rate: $109.25/hr on W2
• Stakeholder Communication: Maintain regular updates and transparency across teams; deliver weekly reports detailing project status, achievements, risks, and review process insights.
• Risk & Mitigation Management: Identify, mitigate, and escalate project risks early, particularly those impacting review timelines and key dependencies.
• Asset Cataloging & Analysis: Research, catalog, and annotate AI Research assets with high attention to detail. Utilize Google Sheets/Excel for data exploration and workflow optimization.
• Domain Awareness: Stay current on developments in the AI research landscape and tooling to continuously improve project outcomes.
• Minimum of 5 years of experience in Technical Program Management and compliance reviews at a technology company with focus on AI
• Exceptional verbal and written communication skills with proven ability to manage stakeholders, persuade, and build consensus.
• Strong ability to work independently, manage time effectively, solve complex problems, and thrive in ambiguous environments.
• Proficiency in Google Apps, Microsoft Office, web browsers, and AI productivity tools and with advanced skills in Google Sheets/Excel for data annotation and analysis.

From the employer

Technical Project Manager II Location: 3 days onsite in Menlo Park, CA or San Francisco, CA Duration: 12-month contract with possibility for extension Pay Rate: $109.25/hr on W2 Benefits: Medical, dental, vision; paid vacation/sick leave, 401k Oversee business-critical projects in the AI Research space, focusing on facilitating review and approval processes to initiate and ship projects. Requires operational excellence, stakeholder management, and the ability to navigate ambiguity across multiple concurrent initiatives. Responsibilites: • Project Ownership & Delivery: Lead multiple project compliance reviews for frontier research, draft requirements, monitor daily progress, manage action items, and proactively resolve blockers to keep milestones on schedule. • Process & Review Optimization: Collaborate with requesters, engineering, research team and reviewers to clarify requirements, streamline approval stages, and coordinate with privacy stakeholders to document best practices. • Stakeholder Communication: Maintain regular updates and transparency across teams; deliver weekly reports detailing project status, achievements, risks, and review process insights. • Risk & Mitigation Management: Identify, mitigate, and escalate project risks early, particularly those impacting review timelines and key dependencies. • Asset Cataloging & Analysis: Research, catalog, and annotate AI Research assets with high attention to detail. Utilize Google Sheets/Excel for data exploration and workflow optimization. • Domain Awareness: Stay current on developments in the AI research landscape and tooling to continuously improve project outcomes. Required Qualifications: • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field required. MBA or advanced degree preferred. • Minimum of 5 years of experience in Technical Program Management and compliance reviews at a technology company with focus on AI • Exceptional verbal and written communication skills with proven ability to manage stakeholders, persuade, and build consensus. • Strong ability to work independently, manage time effectively, solve complex problems, and thrive in ambiguous environments. • Proficiency in Google Apps, Microsoft Office, web browsers, and AI productivity tools and with advanced skills in Google Sheets/Excel for data annotation and analysis. Nice to Have Qualifications: • Background in Privacy and Compliance Reviews, (Generative) AI, Data Analytics, Data Annotations, or Risk Management. • Hands-on experience running ad-hoc queries, analyzing data, and using AI agents and research tools. • Data collection annotation experience is preferred #TMMT