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Venice is a consumer AI company built on principles of privacy, free speech, and user sovereignty. The company is building a platform where millions of individuals, third-party apps, and AI agents can access sophisticated AI resources on a private and permissive foundation.
You will own the model portfolio end-to-end across all of Venice's products (Chat, API, Studio). This is not an ML research role—Venice does not train models. Instead, you will treat models as SKUs, making strategic decisions about what to offer, how to position each one, and how to deliver the best experience across every product.
Key responsibilities include:
• Own the complete model portfolio: decide which models live on the platform, define tiering across free, Pro, Pro Plus, and Max tiers, and maintain the offerings matrix by product line.
• Build the models-as-product operating system: establish launch processes including pre-release testing, configuration review, documentation, and launch communication. Define config standards, uptime SLAs, deprecation policies, and runbooks.
• Drive reliability: define health standards for every model tier, monitor uptime and fallback performance, triage incidents, lead post-mortems, and ensure load-bearing models have appropriate provider redundancy.
• Identify and scope new product offerings: spot opportunities where Venice should build or offer new model products, and turn those into scoped, actionable bets.
• Be the expert on all models: continuously monitor the entire catalog against what providers are actually offering, flag drift immediately, recommend changes, drive decisions, and ensure they ship.
• Own model strategy for each product: understand how users behave, what they ask for, which models they gravitate toward, and map models to use cases across every Venice product.
• Convert evaluation results, usage patterns, and customer feedback into prioritization recommendations. Evaluate and benchmark models to ensure they meet Venice's uncensored, privacy-first standards.
• Work across the organization: collaborate closely with Engineering, API, Business Intelligence, Product Management, and Marketing.
You will report to the VP of Business Operations and serve as the central point of contact for all external-facing products regarding model selection, reliability, configuration, and lifecycle management.
REQUIREMENTS:
• 5+ years in product management, ideally across infrastructure, dev tools, or AI/ML platforms
• Real technical fluency: ability to triage model and configuration issues before escalating to engineering; understanding of model performance metrics and ability to dig deep into error root causes
• Think in unit economics: can reason about COGS and margin per inference request, and make cost/speed trade-off decisions with incomplete data
• Experience operating in ambiguous, fast-moving environments; ability to bring durable operating mechanisms (owners, decision criteria, dashboards, runbooks)
• Comfortable with tooling: APIs, inference systems, observability data, evaluation tooling, and cross-functional launch processes. Bonus: experience with model configurations or AI infrastructure
• Alignment with mission: understand what uncensored model testing and privacy-first positioning require operationally, and believe in their product advantages
