- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 8 years of experience in program management.
- Experience with AI model training, testing, evaluation, and tuning processes, Large Language Model (LLM) release cycles and timeline management.
- Experience in KPIs for AI products.
- Experience with ML/AI principles and their distinctions from traditional software development, and experience translating technical concepts into strategy.
Preferred qualifications:
- 10 years of experience managing complex cross-functional or cross-team projects.
- Experience working on agentic frameworks and products.
- Experience managing customer relationships and promoting best practices.
- Demonstrated track record of managing work streams and ensuring alignment on key milestones and strong problem-solving and strategic thinking skills to navigate rapidly changing programs.
- Exceptional stakeholder management skills, with the ability to influence cross-functional teams without direct authority.
Responsibilities
- Be an innovative thinker capable of navigating organizational complexity. Highly motivated TPM with exceptional problem-solving skills and deep contextual knowledge to lead our generative AI delivery efforts, spanning agent platforms, gemini enterprise, and model deployment.
- Manage programs with deep technical and product understanding, applying program management to complex AI contexts while providing thought leadership.
- Manage end-to-end life cycles, from requirement gathering and risk assessment to feature prioritization.
- Partner with engineering and program manager to define workstreams, resource plans, project milestones. Drive feature planning, building cohesion and alignment across all stakeholders.