Senior Product Manager (AI division)

Tango Analytics is focused on helping businesses make smarter decisions through technology and data. They are seeking a Senior Product Manager for their AI division to own product areas, partner with engineering, and design trust surfaces for enterprise customers.

Responsibilities:

• Own AI product areas within Tango's intelligence layer: define what to build, write acceptance criteria including accuracy thresholds and human-in-the-loop requirements, and ship features with the AI Engineering team
• Partner with AI Engineering as a peer. Earn credibility through product judgment and evaluation standards. Your evaluation framework ships before the feature does
• Design trust surfaces for enterprise customers: confidence disclosure, citation standards, audit trails, and explainability are product decisions you own
• Run discovery with enterprise customers through design partner conversations, usage data analysis, and competitive landscape tracking. Your discovery changes what gets built
• Frame AI investment in customer outcome terms: retention impact, expansion signal, time-to-value. Be clear about what's not on the roadmap and defend the decision
• Define enterprise-grade AI guardrails: confidence thresholds, latency requirements, and human-in-the-loop triggers appropriate for customers with compliance obligations
• Continuously evolve organizational and engineering practices to support and grow the Tango intelligence layer

Requirements:

• 5+ years in product management with shipped and validated AI or ML features in a B2B SaaS environment
• Proven ability to partner with AI Engineering as a peer; earns technical credibility through product judgment; understands model behavior well enough to write meaningful acceptance criteria and constraints
• Track record of defining 'ready to ship' before Engineering starts building. Evaluation criteria, guardrail requirements, and trust surface design are PM-owned decisions
• Comfortable operating within a team where a director sets the platform strategy while you own full product area decisions and execution
• Fluent in LLM-specific product patterns: RAG, evaluation frameworks, prompt versioning, latency/cost trade-offs, and human-in-the-loop design. Keeps abreast of current best practices and developments
• Uses AI tools actively in daily workflow as demonstrated practice, not theoretical interest
• Experience designing enterprise trust surfaces: confidence disclosure, citation standards, explainability, and audit trails for users with compliance obligations
• Can translate dense technical concepts such as model behavior, evaluation methodology, and infrastructure constraints into clear product decisions and crisp stakeholder communication
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience
• Enterprise SaaS experience with complex data workflows, platform infrastructure, or multi-tenant environments strongly preferred