Senior Product Manager, Inference
Together AI is hiring a Senior Product Manager, Inference in San Francisco, United States. It pays $250k-$300k a year and Level rates it ; you can apply on Together AI.
Level's read on this job
- Level rates this AI product manager role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Pay on this posting starts 40% higher than the typical AI product manager posting on Level.
- The posting mentions Cursor, Elevenlabs and Decagon among its tools and skills.
- Level classes it as a senior role.
- Together AI has 77 other open roles on Level.
AI in this role
About the Role
Inference is a critical part of Together AI’s vision and growth strategy. Developers and enterprises use Together to run leading open models across coding agents, AI-native applications, enterprise workflows, and large-scale production workloads.
We’re looking for a Senior Product Manager to shape how customers consume and build on Together inference.
As inference becomes a larger part of our business, the product surface is becoming more complex. Workloads span different tenancy, capacity, performance, and modality needs; agentic applications are changing how inference is consumed; and customers increasingly expect deep infrastructure capabilities to translate into predictable, easy-to-use products.
This role owns the product layer between Together’s inference infrastructure and the developers and enterprises consuming it. You’ll help define how our portfolio of inference products fits together, where Together should differentiate, how customers move from experimentation to production, and how the developer experience evolves as workloads become more sophisticated.
This is a hands-on technical product role. You’ll use our APIs and SDKs, study real workloads, test integrations, and work closely with inference platform engineers and researchers to turn infrastructure and model capabilities into clear product decisions and customer experiences.
Responsibilities
- Shape the inference product strategy. Define how Together’s portfolio should serve different customer needs across tenancy, capacity, performance, workload patterns, and modalities.
- Own the developer experience around inference. Improve our APIs, SDKs, compatibility, and integrations across applications, coding agents, frameworks, and developer tools.
- Build for emerging workloads and modalities. Understand how agentic, voice, multimodal, batch, and other workload patterns are changing what customers need from inference infrastructure, and translate those shifts into product direction.
- Turn infrastructure and model capabilities into customer-facing products. Work closely with inference platform engineers and researchers to understand capabilities and constraints across performance, routing, caching, reliability, capacity, and model behavior, and translate them into the right abstractions, guarantees, and controls for customers.
- Connect product decisions to business outcomes. Shape pricing and packaging alongside Finance and GTM, and use adoption, inference consumption, utilization, unit economics, and customer expansion to prioritize where we invest.
- Stay close to customers and the product. Talk with developers and enterprise teams, inspect usage patterns, test workflows yourself, and use that context to form a clear point of view on what we should build and what we should not.
- Drive products from idea to production. Partner closely with engineering, research, sales, partnerships, finance, and other teams to make tradeoffs, align around priorities, launch, and iterate.
Requirements
- Strong product judgment and the ability to take an ambiguous technical problem, identify what matters, make tradeoffs, and develop a clear point of view.
- Meaningful experience building or owning APIs, developer tools, infrastructure, cloud platforms, data systems, AI products, or another technically deep product.
- Strong technical depth and curiosity. You can work credibly with engineers and researchers, reason about system behavior and constraints, and go deeper when the product problem requires it.
- A hands-on operating style. You’re comfortable testing APIs and SDKs, using developer tools, reading technical documentation or code when useful, and building lightweight prototypes or analyses to sharpen your thinking.
- Strong developer and customer empathy. You care about what a system actually feels like to integrate with and operate in production, not just whether the underlying capability exists.
- A track record of making clear product decisions and shipping in fast-moving environments where the right answer is not always obvious.
- Strong communication and cross-functional leadership, with the ability to earn trust across engineering, research, customers, and business teams.
Experience with LLM inference, model serving, distributed systems, GPU infrastructure, agents, or developer-facing AI products is helpful, but not required. We care most about your ability to learn technical systems quickly, get close to the product, and develop strong judgment.
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: $250 - 300k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Application Policy
Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application.
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 https://www.together.ai/privacy.
How we rate this
Senior Product Manager, Inference at Together AI rates 71 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI product manager jobs at this level
Pay
- This job starts at
- $250k
- Typical AI product manager job
- $178k
This posting starts 40% above the typical AI product manager job. See AI product manager jobs
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through how you've used Cursor in your day-to-day work.
- What are the limits of Elevenlabs that you've run into, and how did you work around them?
- What's a project where you used Decagon hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Cursor, Elevenlabs, and Decagon. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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