Sr. Principal Technical Program Manager
G
G-PSaaS
United States (Remote-First)Full-TimePrincipal
Salary176,000 - 221,000 USD per year
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Job Details
- Experience
- Minimum of 10 years of experience
- Required Skills
- JiraRelease ManagementConfluenceGoogle WorkspaceGenerative AI
Requirements
- Minimum of 10 years of experience in SaaS product development, program management, and release management.
- Direct experience with AI-driven development lifecycles and utilizing AI/Agentic workflows to optimize program management architectures.
- BS in Computer Science, Engineering, Statistics, or a related technical field.
- Proven ability to earn trust quickly, mobilize teams, and set direction in highly ambiguous environments.
- Ability to deliver tough messages with grace, resolve conflict, and adapt to change rapidly.
- Experience and familiarity with industry-standard project management software (e.g., Jira, Confluence, Google Suite).
- Deep proficiency in the rapidly evolving AI landscape (LLMs, generative AI, agentic frameworks) with a demonstrated ability to integrate these capabilities into practical, future-proof program management strategies.
- Effective presenter, negotiator, and collaborator who can communicate with clarity and precision at all levels of the organization.
- A strategic mindset equally passionate about business outcomes and deep technology.
Responsibilities
- Manage multiple concurrent programs varying in size and complexity, maintaining objective oversight while demonstrating a deep passion for the program's success.
- Ensure every program aligns to a strict Program Playbook—meaning the technical capability is successfully delivered and the targeted outcomes are fully realized.
- Establish a consistent execution rhythm and rituals to force decision-making, remove blockers, and clarify ownership.
- Act as an "information radiator," utilizing clear reporting systems to communicate delivery health, milestone tracking, and look-ahead risk analysis to leadership.
- Integrate AI seamlessly into your program management workflows, such as utilizing AI and agentic tools to automate RAID (Risks, Actions, Issues, Decisions) logs and synthesize status updates into concise executive summaries.
- Govern the inherent unpredictability of AI development, adapting traditional program management to account for experimentation.
- Maintain a centralized Work Surface (e.g., Jira, Confluence) as the ultimate hub for tracking initiative status, critical paths, and dependencies.
- Identify and overcome delivery roadblocks in a complex environment, escalating risks quickly and effectively.
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