Fastly
Staff Product Manager, Storage & Edge Data
San Francisco, CA · Staff+
Sponsorship not specified$211k-$254kDetected 9 days ago
Distributed SystemsGitCloud PlatformsComputer VisionProduct ManagementProduct StrategyAgileNegotiationVendor ManagementResearchCommunication
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odds of building a lasting career here
59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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Files H-1B transfers
4 transfer filings in the last year, covering 4 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- Fastly helps people stay better connected with the things they love.
- Posting Open Date: 10/7/2026 Anticipated Posting Close Date*: 12/15/2026 *Job posting may close early due to the volume of applicants.
- This role will have a significant impact on Fastly's strategic initiatives, customer satisfaction, and revenue goals.
Responsibilities
- Collaborate on a cross-functional roadmap for Fastly's key product capabilities, working with other product and engineering teams to ensure platform-wide consistency and success between storage and edge data offerings
- Collaborate with Sales and Product Marketing to drive product growth via cross-functional training and coordinated campaigns
- Collaboratively lead cross-functional and distributed teams by building trusted working relationships throughout the company, at all levels of the organization
- Fastly works hard to create a positive environment for our employees, and we think your life outside of work is important too.
- Not only do our customers have a tremendous user base, but we also support a growing number of open source projects and initiatives.
Requirements
- Bachelor's degree in Computer Science, Mathematics, or equivalent experience
- 5-8 years of product management experience
- Experience working on large-scale distributed systems, cloud storage, data infrastructure, networking, or security
- Familiarity with object storage, S3-compatible APIs, or key-value/data store technologies
- A fully completed application and resume or CV are required when applying.
- All job applications must be submitted through our official careers site at www.fastly.com/about/careers.
Compensation
- The estimated range for On-Target Earnings for this role is $211,370.00 to $253,644.00.
- Starting salary may vary based on permissible, non-discriminatory factors such as experience, skills, qualifications, and location.
Benefits
- We support our teams with great benefits that start on the first day of your employment with Fastly.
- We offer a comprehensive benefits package including medical, dental, and vision insurance.
- We also offer 401(k) (including company match) and an Employee Stock Purchase Program.
- For 2026, we offer 11 paid local holidays, 11 paid company wellness days.
- Consistent with the Americans with Disabilities Act (ADA) and federal or state disability laws, Fastly will provide reasonable accommodations for applicants and employees with disabilities.
Company info
- Fastly's customers include many of the world's most prominent companies, including GitHub, Yelp, Paramount, and JetBlue.
- We are committed to being a company where our employees feel comfortable bringing their authentic selves to work and have the ability to be successful -- every day. - We are passionate.
- Define the strategy and roadmap for Fastly Object Storage and our edge data products, partnering with stakeholders across the organization to deliver these products for customers
- What We're Looking For:
- We are committed to being a company where our employees feel comfortable bringing their authentic selves to work and have the ability to be successful -- every day.
- We are passionate.
This listing is sourced directly from Fastly's careers page and normalized into a canonical job model.