Director of Product, A.Team

• 0 to 1 product building - you've taken products from early stage to enterprise-ready
• Engineering & data science collaboration - you've worked hands-on with engineering and data science teams to build complex technical products or APIs
• Sales pipeline integration - you've partnered with Marketing & Sales, been ingrained in the sales pipeline to identify product opportunities (new products and application of existing capabilities)
• Enterprise B2B product experience - you understand what enterprises actually need vs. what they say they need

Desirable

• We have an Agentic OS that's proven in customer POCs and generating real enterprise contracts. But there's a huge gap between "it works in the demo" and "it consistently delivers transformational value." We need someone who can bridge that gap and turn field learnings into product features that actually matter
• This isn't about building a product from scratch - it's about taking something that already works and making it bulletproof for enterprise deployment. You'll work directly with our Engineering and AI Architect lead to figure out what comes next, based on real customer data, not just product manager intuition
• Product Roadmap & Prioritization: Own the Agentic OS product roadmap based on customer deployment data, engineering capacity, and market opportunities. Make the hard calls about what we build vs. what we don't
• Customer-Driven Feature Development: Transform field learnings from our forward-deployed teams into specific product requirements. Turn "the client needs X" into buildable engineering specifications
• Sales Pipeline Product Intelligence: Partner directly with Marketing & Sales to identify product gaps, competitive threats, and new product opportunities from active deals and lost opportunities
• Engineering & Data Science Collaboration: Work hands-on with engineering and data science teams to build complex technical products, APIs, and integrations that enterprise customers actually need
• Continuous Product-Market Fit Optimization: Use deployment metrics, customer success data, and sales feedback to continuously refine our AI Controller, AI Data Engineer, and AI Data Scientist capabilities
• Success Looks Like:
• Product-market fit: Clear evidence that enterprises can't say no to our offering
• Competitive advantage: Maintain clear technical differentiation from incumbents
• Enterprise readiness: Platform capabilities that support big deals
• Customer satisfaction: Deployments that consistently deliver promised value
• You're building the product that defines how enterprises adopt AI
• Work with real customer deployments, not just user feedback surveys
• Your decisions directly impact million-dollar deals and customer transformations
• Collaborate with cutting-edge AI research and engineering
• We're not a traditional corporate environment where everything goes through committees