Technical Product Marketer, Developer Products

About the role

Krisp is seeking a Technical Product Marketer to shape the narrative for its developer‑focused Voice AI products. You will collaborate closely with research and engineering teams to translate complex technical work into compelling stories for developers and technical buyers.

Key responsibilities

• Own positioning and messaging for Krisp’s developer products.
• Lead launches of new models, APIs, SDK capabilities, and major research improvements.
• Manage benchmark launches, working with research teams on methodology, datasets, metrics, results, and limitations.
• Convert technical results into benchmark pages, launch posts, product pages, demos, and developer‑facing content.
• Partner with researchers and engineers to highlight genuine differentiation and ensure technical accuracy.
• Create technical sales and partner enablement materials.
• Collaborate with Growth and Developer Marketing to distribute content via search, GitHub, developer communities, newsletters, Hacker News, Reddit, and other channels.
• Monitor the Voice AI market and feed customer, developer, and competitive insights back into product positioning and launches.

Required profile

• 3–5+ years of experience in technical product marketing, developer marketing, product management, engineering, or developer relations.
• Strong technical foundation with comfort around APIs, SDKs, AI/ML concepts, latency, model evaluation, datasets, benchmarks, and performance metrics.
• Proven ability to work directly with researchers, ML engineers, and developers and speak their language.
• Experience marketing technical products to developers, engineers, or technical buyers.
• Excellent storytelling and writing skills, turning complex technical results into clear, memorable ideas.
• Track record launching technical products, AI models, APIs, SDKs, or infrastructure solutions.
• Analytical judgment around benchmarks, quantitative claims, and technical proof.
• Hands‑on, curious, and comfortable moving between strategy and execution.

Required skills

• APIs
• SDKs
• AI/ML concepts
• Model evaluation
• Datasets
• Benchmarks
• Performance metrics