About AQe Digital :

AQe Digital builds and scales digital products for global clients through strong product engineering, design, and data capabilities. We are developing an AI-led product organization focused on delivering scalable SaaS products with measurable business impact.

Role Overview :

- The Senior Product Manager owns product strategy and execution for a defined product area. This role focuses on customer value, delivery excellence, and revenue outcomes, while contributing to an AI-driven product roadmap.

- The Senior PM works closely with Engineering, UX, Data/AI, Sales, Marketing, and Customer Success teams to deliver high-quality, scalable SaaS products.

Key Responsibilities :

- Product Strategy & Delivery

- Contribute to product vision, strategy, and quarterly or multi-year roadmaps.

- Identify and prioritise features that drive adoption, retention, and revenue growth.

- Translate business and customer needs into epics, user stories, and acceptance criteria.

- Own backlog management, prioritisation, and readiness for development.

- Act as Product Owner within Agile/Scrum teams and lead sprint ceremonies.

- Track product performance metrics and apply insights to roadmap decisions.

- Cross-Functional Collaboration

- Partner with UX to design intuitive user journeys and workflows.

- Work with QA to ensure high-quality, production-ready releases.

- Collaborate with Sales, Marketing, and Customer Success on GTM, adoption, and feedback loops.

- Work with Service Delivery teams to identify repeatable solutions suitable for productisation.
- AI-Led Product Expectations

- AQe Digital expects Product Managers to make AI and data central to product evolution.

- The Senior Product Manager will :

- Identify AI and data-driven opportunities within their product domain.

- Partner with data scientists and ML engineers to productize AI capabilities.

- Define success metrics and feedback loops for AI-powered features.

- Track AI-specific metrics such as model quality, automation rates, and error rates.

- Ensure responsible and explainable use of AI, especially in regulated or sensitive contexts.

- Use AI-driven insights to inform prioritisation and product decisions.

Candidate Requirements :

- Core Product Management

- 5+ years of experience as a Product Manager or Product Owner(total of 8-12 years).

- Strong experience working on SaaS or B2B products.

- Hands-on experience with Agile/Scrum delivery.

- Strong ability to write epics, user stories, and acceptance criteria.

- Business & Execution Skills

- Understanding of product and revenue metrics (usage, retention, growth).

- Ability to manage ambiguity and complexity.

- Strong analytical and problem-solving skills.

- Clear communication with technical and non-technical stakeholders.

Qualifications (Preferred) :

- Bachelors degree in Engineering, Computer Science, Business, or equivalent.

- Exposure to AI-enabled or data-driven products.

Requirements :

Must Have :

Core Product Management :

- Bachelors in engineering, Computer Science, or equivalent

- 36 years experience in a Product Manager role, preferably within marketplaces, SaaS, or startup environments.

- Full lifecycle experience with MVP or 0-to-1 product launches.

- Practical experience in Agile/Scrum frameworks, with a proven track record as a Scrum Product Owner.

AI/ML Product Experience :

- 2+ years of experience managing AI/ML-powered products or working closely with data science teams.

- Understanding of machine learning concepts supervised/unsupervised learning, model training, validation, and deployment.

- Experience defining success metrics for AI/ML models and translating model outputs into user-facing features.

- Familiarity with A/B testing methodologies for AI-driven products and data-driven decision making.

- Knowledge of data collection, labelling, and quality management for training AI models.

Technical & Collaboration Skills :

- Strong ability to work in and coordinate cross-functional teams (engineering, design, data/AI).

- Technical fluency to communicate effectively with data scientists and ML engineers about model requirements and performance.

- Solid understanding of product analytics, user testing, iterative development, and rapid prototyping.

- Excellent communication, stakeholder management, and problem-solving abilities.

Preferred Qualifications :

- Experience with recommendation systems, matching algorithms, or marketplace AI applications.

- Familiarity with ML model monitoring tools, MLOps practices, and AI ethics frameworks.

- Experience in packaging, manufacturing, B2B supply chain, or similar industry verticals.

- Background in startups, small teams, or resource-constrained innovation projects.

- Understanding of real-time AI systems