Job description

About the Role Our product surface is expanding fast - GPU clusters, managed storage, networking, and observability - and we're adding a Product Manager to the Together Cloud team to own the day-to-day product work that keeps these AI infrastructure products moving. You'll start across the full surface, with an early focus on observability and GPU Clusters, partnering closely with engineering to ship the feature work that customers feel every day. This is a role for someone who runs toward problems. You won't be handed a backlog and asked to coordinate it - you'll find the issues others haven't spotted yet, drive them to resolution, and use data and experimentation to decide what to build. You'll have real autonomy from day one, and the breadth of working across compute, storage, and observability that few PM roles offer. It's also a role with a clear path. Within roughly nine months, the goal is for you to grow into full ownership of a complete product area — observability or storage as your own. You'll report directly to a Staff Product Manager, and our product leadership (including our CPO) is closely involved with this team. If you want to build infrastructure that the AI ecosystem runs on, and earn ownership quickly by proving you can operate, this is that seat. 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. Requirements Deep empathy for customers operating in high-ambiguity, fast-evolving markets; we work with AI Native startups and model labs that move at high pace Strong, hands-on data and analytics skills with a hypothesis-driven approach - you design experiments, read the data yourself, and can drive the data collection needed to get answers. High agency: you find problems, push through resistance, and drive resolution without waiting to be told what to do. A real technical foundation -whether from an AI/infrastructure background, hands-on software development, or strong working knowledge of cloud and infrastructure. A track record of collaborating across orgs and product lines to get things done. Comfortable managing multiple priorities and workstreams at once. 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: working knowledge of the Nvidia/AMD GPU stack (InfiniBand, NCCL, GPU operator, etc.), or experience with AI training or inference workloads. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $ 175,000 - 220,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at together.ai .

Requirements

Must-haves

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.
Deep empathy for customers operating in high-ambiguity, fast-evolving markets; we work with AI Native startups and model labs that move at high pace
Strong, hands-on data and analytics skills with a hypothesis-driven approach - you design experiments, read the data yourself, and can drive the data collection needed to get answers.
High agency: you find problems, push through resistance, and drive resolution without waiting to be told what to do.
A real technical foundation -whether from an AI/infrastructure background, hands-on software development, or strong working knowledge of cloud and infrastructure.
A track record of collaborating across orgs and product lines to get things done.
Comfortable managing multiple priorities and workstreams at once.
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.

Nice-to-haves

Bonus: working knowledge of the Nvidia/AMD GPU stack (InfiniBand, NCCL, GPU operator, etc.), or experience with AI training or inference workloads.

Application prep

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Keywords to mirror

aiawsazuregcp

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance