Product Manager, AI Infrastructure
Together AI· Product
Hybrid (San Francisco)$175k - $220kfull-timePosted 3mo ago
About the role
Product Manager to own day-to-day product work across Together AI infrastructure products (GPU Clusters, Managed Storage, observability), with early focus on observability and storage; role emphasizes problem discovery, hypothesis-driven experimentation, and fast ownership growth toward a complete product area (observability or storage).
Responsibilities
- Own the day-to-day product and feature work across Together's AI infrastructure products - GPU Clusters, Managed Storage, and observability - with an early focus on observability and storage.
- Find and drive problems to resolution with minimal guidance, including issues that aren't yet on anyone's radar.
- Run structured, hypothesis-driven experiments - reading the data yourself and driving the data collection and instrumentation needed to answer open questions.
- Partner across engineering, product, and partner teams to ship improvements and unblock work without waiting for permission.
- Translate a deep understanding of customers operating in fast-moving, high-ambiguity markets into product decisions.
- Juggle multiple priorities and workstreams across a broad infrastructure surface.
- Grow into end-to-end ownership of a complete product area (observability or storage) as you ramp.
Qualifications
- Deep empathy for customers operating in high-ambiguity, fast-evolving markets; experience with AI Native startups and model labs that move at high pace.
- Strong, hands-on data and analytics skills with a hypothesis-driven approach - design experiments, read the data yourself, and drive data collection to get answers.
- High agency: identify problems, push through resistance, and drive resolution without waiting to be told what to do.
- Real technical foundation - AI/infrastructure background, hands-on software development, or strong working knowledge of cloud and infrastructure.
- Track record of collaborating across orgs and product lines to get things done.
- Comfortable managing multiple priorities and workstreams.
- Familiarity with the AI stack, especially at the infrastructure layer, is a strong plus.
- Cloud platform experience (AWS, Azure, GCP, or similar) - with extra weight if you've helped build such products.
- Bonus: knowledge of Nvidia/AMD GPU stack (InfiniBand, NCCL, GPU operator, etc.), or experience with AI training or inference workloads.
Skills
Required:Customer empathy in high-ambiguity marketsHypothesis-driven data analysisTechnical foundation in AI/infrastructureCross-org collaborationCloud platform experience
Nice to have:GPU stack / AI workload knowledge
Benefits
- competitive compensation
- startup equity
- health insurance and other competitive benefits
Last updated Sep 9, 2026. Interested? Apply on the company site.
About Together AI
The AI Acceleration Cloud - Fast Inference, Fine-Tuning & Training
Run and fine-tune generative AI models with simple APIs and scalable GPU clusters. Train & deploy at scale on The AI Acceleration Cloud.
AI native cloudFine-TuningGPU clustersInferenceTrainingai-infrastructure-and-developmentbrex-fastest-growing-2025liquid-ai-recruiting-target
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