Owns the strategy, roadmap, discovery, delivery, and adoption of enterprise Generative AI and analytics products. Partners with engineering, data science, UX, security, legal, and business teams to deliver AI assistants, conversational interfaces, natural language analytics, and developer productivity tools. Defines evaluation frameworks, KPIs, governance, responsible AI practices, and value realization models while driving stakeholder alignment, organizational adoption, and continuous product improvement.
What Success Looks LikeUser Adoption
Responsibilities- Increase active engagement across business users, analysts, developers, and operational teams.
- Demonstrate sustained growth in product adoption and usage.
- Deliver reliable AI experiences with measurable improvements in response quality, relevance, and user satisfaction.
- Establish evaluation frameworks that ensure transparency and confidence in AI-generated outputs.
- Improve business, analyst, and developer productivity through AI-powered automation and insights.
- Reduce manual effort and accelerate access to information and decision support.
- Enable onboarding of additional domains, functions, and teams through reusable AI capabilities and improved metadata quality.
- Increase organizational readiness for enterprise AI adoption.
Product Strategy and Vision
Qualifications- Define and execute the product strategy, roadmap, and long-term vision for AI enablement capabilities.
- Identify opportunities where AI can improve productivity, automation, insight generation, and user experience.
- Align product priorities with business objectives and enterprise digital transformation strategies.
- Conduct research with business users, analysts, engineers, developers, and operational stakeholders.
- Identify user pain points and opportunities through data-driven discovery and experimentation.
- Translate customer needs into product requirements, user stories, epics, and measurable success criteria.
- Partner closely with engineering, data science, UX, and platform teams to develop and launch AI-powered products.
- Guide development of conversational interfaces, AI assistants, natural language analytics, and developer productivity tools.
- Define experimentation frameworks and evaluation methodologies for AI capabilities and model performance.
- Establish KPIs and success measures focused on adoption, engagement, productivity, quality, trust, and operational efficiency.
- Monitor product outcomes and continuously optimize based on user feedback and behavioural insights.
- Develop business cases and value realization frameworks for AI investments.
- Champion Responsible AI principles, governance frameworks, and compliance requirements.
- Promote metadata quality, knowledge management, explainability, and trustworthy AI practices.
- Partner with security, legal, and governance stakeholders to ensure policy compliance.
- Build strong partnerships across business functions, technology organizations, and senior leadership.
- Communicate product vision, strategy, roadmap, risks, and outcomes effectively to executive and technical audiences.
- Drive organisational adoption and change management activities for AI-powered capabilities.
- Required
- Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or a related field.
- 8-10 years of Product Management experience.
- Demonstrated experience delivering AI, analytics, data, or developer-focused products.
- Strong understanding of Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), and conversational interfaces.
- Experience defining product strategy, roadmaps, and outcome-based success metrics.
- Strong stakeholder management and cross-functional leadership skills.
- Experience working with engineering, machine learning, user experience, and business teams.
- Excellent written, verbal, presentation, and storytelling skills.
- Experience launching enterprise AI or Generative AI products at scale.
- Experience with cloud platforms such as Azure, Google Cloud Platform (GCP), or AWS.
- Familiarity with enterprise data platforms, analytics ecosystems, and knowledge management solutions.
- Experience defining evaluation frameworks for AI quality, trust, and model performance.
- Prior experience in developer productivity, internal platforms, or enterprise tooling products.
- MBA or advanced degree in a related discipline.
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