Senior Product Manager, Inference

What We're Looking For

We're looking for a Founding Product Manager for Inference who will own this product end-to-end—roadmap, pricing, and GTM—from the ground up. This is a zero-to-one role at the intersection of deep technical fluency and commercial instinct. You'll define what we build and why, design the developer journey from first API call to production workload, and be the product voice in sales cycles and the market.

The right candidate has lived inside the machine; they've operated model serving infrastructure or shipped products on top of it, and can move fluidly between a latency/throughput tradeoff conversation with an infra engineer and a positioning conversation with a sales lead. You will be joining the Product Team and report to our VP of Product working directly with our executive team as we grow this business. 

This is a hybrid role based in our New York City or San Francisco office with in-office requirements of 2 days per week. 

What You’ll Do

• Define Lightning AI's inference product vision and roadmap — what we build, what we don't, and in what order — translating the competitive landscape (vLLM, Together, Fireworks, Modal, hyperscaler inference APIs) into a differentiated strategy grounded in Lightning's compute and software advantage
• Own inference pricing and packaging end-to-end: design the model (per-token, per-second, reserved capacity), run pricing experiments with Growth and Finance, and define the tiers that convert self-serve developers into enterprise contracts
• Be the product voice in GTM: develop sales positioning, answer technical objections in the field, and partner with Marketing on the benchmarks, reference architectures, and developer content that builds credibility with ML engineers and platform teams
• Own the developer journey from API key to production-scale deployment — identify and remove friction across onboarding, documentation, SDK ergonomics, and dashboard observability
• Lead experiments across activation flows, pricing pages, and upgrade prompts; track and move DAU/MAU, Time to Value, Activation %, PQLs, and expansion revenue
• Partner with engineering to write tight specs and make fast build/buy/partner decisions; collaborate across Product to ensure inference coheres with training, fine-tuning, and storage surfaces
• Establish inference-specific metrics — throughput, latency SLAs, cold-start behavior, cost per token — and build the instrumentation to track them

What You’ll Need

• 7+ years of product management experience, with at least 3 years in infrastructure, platform, or developer tooling products
• Direct, hands-on experience with model serving or inference infrastructure — you've shipped in this space; you understand quantization, batching strategies, KV cache, and speculative decoding at a level that lets you go deep with ML engineers
• Proven track record owning product pricing and packaging decisions, not just feature decisions — you've modeled unit economics and made calls that affected margin
• Experience with a PLG or trial-to-paid motion in a developer product; you know how to build self-serve growth loops and run rigorous A/B experiments
• Strong analytical skills — comfortable with product instrumentation, metrics, and dashboards; you pull your own data
• Excellent written and verbal communication; you can write a crisp one-pager, a technical spec, and a customer-facing benchmark brief with equal fluency
• Bias for action and comfort operating with high ambiguity in a fast-moving environment
• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)
• Bonus: Prior experience at a neocloud, hyperscaler inference team, or AI infrastructure startup; familiarity with the PyTorch/Lightning ecosystem; background in GPU cluster products or consumption-based infrastructure pricing

Compensation