Product

About Gradium

Gradium is a frontier voice AI company on a mission to redefine how humans interact with machines.

Voice remains the most human, highest-stakes channel, but also the most broken. Long wait times, rigid IVRs, low automation, and poor handoffs create frustration on both sides of the line. Gradium is rebuilding voice from the ground up with proprietary models: real-time understanding, autonomous resolution, and seamless escalation when humans matter most.

We're a team of world-class talent, with initial traction and a clear belief: voice will be the next major frontier of applied AI. We recently raised a $100m seed round and are backed by top-tier investors. Our goal is not incremental improvement: it's to make AI-powered voice interactions feel reliable, scalable, and economically transformative.

Expect early-stage reality: high autonomy, fast decisions, unreasonable ambition, few handoffs, and very little process unless it earns its place.

The Role

We're looking for the founding members of our Product team to own a core surface of Gradium's product: the quality, reliability, and experience of the models our customers build on.

Depending on your strengths and where we need you most, that scope could center on any of our model families (text-to-speech, speech-to-text, speech-to-speech, live translation) or on the voice catalog, studio and website experience that sits on top of them. Across all of them, the job has the same shape: turn a model that's impressive in a demo into something that holds up in production, on real customer content, on every API call.

You'll work hand in hand with the founders, research, and engineering to make our models "bulletproof" before anything reaches customers. This role exists because our biggest constraint is no longer whether we can build great voice technology, but how fast and how reliably we turn it into product customers trust.

What You'll Do

• Act like a founder and own your surface end to end: Set the roadmap, prioritize ruthlessly, and drive it from problem to shipped. You decide what ships next and why, keep research and engineering aligned, and set the tempo for model cycles and releases. Nobody hands you a backlog, you build it.

• Own quality and make it measurable: Define what "great" means for your focus area (e.g. pronunciation accuracy and stability, voice naturalness, transcription quality) and build the evaluation that proves it. You'll extend that rigor into new areas, objectifying quality where it's subjective today.

• Make the pipeline do the work: Our product team owns the last step of our eval pipeline that measures every model iteration before it ships, catches regressions before customers do, and increasingly gates releases automatically. You'll turn results into honest benchmarks, live dashboards, and "wow" demos.

• Stay close to customers and turn their pain into priorities: Get deep on what customers actually struggle with: pronunciation failures, hallucinations, latency, finding the right voice. Translate it into a prioritized problem set for research and engineering. Arm the sales team with the demos, evidence, and quality answers that move deals forward.

• Ship the experience, not just the model: Own how customers encounter your work in the product from the voice catalog, its taxonomy and search, to the studio, onboarding, and developer experience. Make it effortless for a developer to go from first listen to production with zero surprises.

• Work in an AI-native way: Use AI-assisted tools for prototyping, analysis, and evaluation, from automated quality scoring to vibe coding. Push the team to adopt AI-native workflows wherever they accelerate speed or improve output.

Who You Are

• Founder mindset: You act with urgency, take full ownership, and don't wait for permission or perfect information. You are comfortable making high-stakes decisions in ambiguous environments and see the founding team as partners, not hierarchy.

• Proven track record: You've shipped a generative AI product with real impact. You get model evaluation, output variance, and the challenges of non-deterministic systems, and you know a demo from a production-grade feature.

• Technically fluent: You can hold your own with research and engineering on model behavior, software architecture, data, and infrastructure. You understand “what an API is” and who developers are, and you can reason about latency, accuracy, and reliability trade-offs.

• AI-fluent operator: You use AI-powered tools and, more important, you can always articulate why. You're not chasing novelty. You care about the impact it creates. You're relentless about pushing what's possible and reinventing how you and your team operate.

• Rigor and quality at scale: You bring structure to ambiguous problems, defining metrics, and setting standards that hold a high bar as throughput grows. You think in systems and automation, not one-off process, and you've found ways to get both speed and craft.

• Strong taste:You know good from great when you see it or hear it, and you trust that judgment. Data tells you what's working, but taste tells you what's worth building in the first place.