Senior Product Manager (SaaS, AI)

Role

Lead the conception, roadmap, and delivery of data and AI products for a B2B SaaS platform. Translate AI research into scalable features, work closely with engineering to design production-ready solutions, engage customers for feedback, and validate ideas through rapid prototypes and proofs-of-concept.

Key Responsibilities

• Own product management for data and AI features from discovery through launch and iteration.
• Develop and maintain a clear product roadmap to expand AI offerings and integrate advanced data solutions.
• Analyze large and complex datasets to inform prioritization, measure success, and drive product decisions.
• Translate cutting-edge AI concepts (LLMs, transformers, reinforcement learning) into practical, scalable SaaS capabilities.
• Collaborate with engineering and data science teams to convert AI/ML concepts into actionable product specifications and ensure successful implementation.
• Communicate product vision, strategy, and progress to non-technical stakeholders, executives, and customers.
• Engage customers to gather feedback, drive adoption, and shape product-market fit.
• Rapidly prototype ideas using low-code/no-code and collaborative tools to validate concepts before detailed epics/specs.

Requirements

• 5+ years as a Product Manager focused on data, analytics, or AI products in a B2B SaaS environment.
• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field; advanced degree preferred.
• Proven track record shipping data-driven and AI-powered products with measurable adoption.
• Experience across the AI/ML lifecycle: data acquisition, model training, deployment, and monitoring.
• Strong understanding of data fundamentals: data modeling, data integration, ETL pipelines, and analytics.
• Familiarity with cloud platforms (AWS, Azure, Google Cloud) in enterprise SaaS or cloud marketplace contexts.
• Experience with data analysis and data-driven decision-making; ability to identify data requirements and ensure responsible data use.
• Proficiency in SQL and Python or R for dataset exploration, dashboarding, and A/B experiments.
• Experience building dashboards or analyses with tools like Looker or Tableau.
• Strong user empathy, storytelling through design and data, and excellent verbal and written communication.
• Demonstrated ability to work effectively with cross-functional teams (engineering, data science, UX, go-to-market).

Preferred / Nice to Have

• Experience taking AI/ML models from prototype to production and scaling commercial adoption.
• Experience monetizing data or packaging intelligence into premium product tiers.
• Practical experience prototyping with tools like Replit, Lovable.dev, Windsurf, or similar low-code/no-code platforms.
• Familiarity with large language models and ecosystems (OpenAI GPT, Claude 3.7 Sonnet, Grok, Gemini).
• Knowledge of prompt engineering, LLM tuning, AI ethics frameworks, and bias mitigation.
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn, Keras) and MLOps platforms (AWS Bedrock, MLflow, Databricks, Google Cloud Vertex AI, AWS SageMake).
• Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google ML Engineer).