Senior Product Manager - Inference Platform
New
J
JobgetherAI infrastructure
Based in the United StatesFull-TimeSenior
Salary228,000 - 285,000 USD per year
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Job Details
- Required Skills
- Distributed Systems
Requirements
- Demonstrated experience launching and managing technical platform products from strategy through delivery and adoption.
- Senior-level product management experience leading initiatives across multiple engineering teams.
- Strong technical understanding of AI inference, including model serving, distributed systems, and production infrastructure.
- Ability to analyze technical problems, evaluate trade-offs, and make informed product decisions with engineers.
- Experience working with B2B or enterprise customers, particularly technical buyers.
- Strong communication and stakeholder-management skills across engineering, research, sales, support, and leadership.
- Experience preparing PRDs, RFCs, release notes, and technical product documentation.
- Ability to manage expectations, prioritize competing needs, and maintain cross-functional alignment.
- Comfort working in a fast-moving environment where product scope, technology, and customer requirements can change.
- Strong analytical thinking and a customer-focused approach to product development.
- Experience with model post-training, including training draft models, is an advantage.
- Experience establishing and managing third-party technical partnerships is an advantage.
Responsibilities
- Own the product strategy, roadmap, and measurable outcomes for a core stream of the AI inference platform.
- Coordinate multiple engineering teams working on public APIs, request routing, performance optimization, reliability, and enterprise enablement.
- Partner with engineering and research teams to improve inference scalability, reliability, and cost efficiency.
- Translate technical improvements into platform capabilities for developers and enterprise customers.
- Conduct customer research, interviews, and hands-on proofs of concept, particularly with managed enterprise customers.
- Analyze open-source models, inference economics, hardware developments, and AI adoption patterns to identify product opportunities.
- Turn market insights and customer feedback into prioritized product initiatives and investment decisions.
- Communicate product direction, requirements, trade-offs, and expectations across engineering, research, sales, support, and leadership.
- Develop PRDs, RFCs, release notes, and other documentation to support alignment and delivery.
- Adapt product priorities and execution plans as customer requirements, technologies, and market conditions evolve.
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