Product Manager (AI / Tech Products)
Role summary
We are seeking a Product Manager to drive the vision, strategy, and execution of our AI and Tech Products. This role involves defining the AI product roadmap, identifying high-impact use cases, and translating business problems into AI-driven solutions. You will leverage data to make informed product decisions, manage the full product development lifecycle from ideation to launch, and ensure the integration and performance of AI/ML models. A key aspect of this role is ensuring responsible and ethical AI usage, aligning with regulations and internal policies. You will lead cross-functional teams, including data scientists, engineers, and designers, and act as the bridge between technical teams and business leadership. Additionally, you will develop go-to-market strategies and communicate product progress to executives. This position requires strong Agile execution and a deep understanding of customer needs and market trends.
Role & responsibilities :
1. Product Vision & Strategy
- Define clear product vision aligned with business goals and market needs
- Build and own the AI product roadmap (short-term + long-term)
- Identify high-impact AI use cases (automation, personalization, decision intelligence)
2. AI Use Case Definition & Prioritization
- Translate business problems into AI-driven solutions
- Prioritize features based on:
- ROI
- feasibility
- risk
- Balance innovation vs practical delivery
3. Data-Driven Decision Making
- Use data to guide product decisions:
- user behavior
- model performance
- business metrics
- Define success metrics (KPIs like adoption, accuracy, retention)
4. Cross-Functional Leadership
- Lead collaboration between:
- Data scientists
- Engineers
- Designers
- Business stakeholders
- Act as the bridge between technical teams and business leadership
5. AI Product Development Lifecycle
- Manage full lifecycle:
- Ideation
- Design
- Development
- Testing
- Launch
- Ensure smooth execution of sprints and releases
6. AI/ML Model Integration & Oversight
- Work with teams to integrate models into products
- Define requirements for:
- training data
- model evaluation
- deployment
- Monitor model performance in production
7. Responsible AI & Governance
- Ensure ethical and compliant AI usage:
- bias mitigation
- explainability
- privacy
- Align with regulations and internal policies
8. Product Performance & Optimization
- Continuously improve product based on:
- user feedback
- analytics
- A/B testing
- Optimize accuracy, usability, and business outcomes
9. Customer & Market Research
- Understand customer pain points and market trends
- Conduct interviews, surveys, and competitive analysis
- Translate insights into product features
10. Go-To-Market Strategy
- Define launch strategy:
- pricing
- positioning
- messaging
- Work with sales and marketing teams for successful rollout
11. Stakeholder Communication
- Present product vision, roadmap, and progress to executives
- Communicate trade-offs, risks, and outcomes clearly
12. Agile & Product Execution
- Lead Agile ceremonies:
- backlog grooming
- sprint planning
- retrospectives
- Ensure timely delivery of features
Preferred candidate profile :
1. Product Vision & Strategy
- Define clear product vision aligned with business goals and market needs
- Build and own the AI product roadmap (short-term + long-term)
- Identify high-impact AI use cases (automation, personalization, decision intelligence)
2. AI Use Case Definition & Prioritization
- Translate business problems into AI-driven solutions
- Prioritize features based on:
- ROI
- feasibility
- risk
- Balance innovation vs practical delivery
3. Data-Driven Decision Making
- Use data to guide product decisions:
- user behavior
- model performance
- business metrics
- Define success metrics (KPIs like adoption, accuracy, retention)
4. Cross-Functional Leadership
- Lead collaboration between:
- Data scientists
- Engineers
- Designers
- Business stakeholders
- Act as the bridge between technical teams and business leadership
5. AI Product Development Lifecycle
- Manage full lifecycle:
- Ideation
- Design
- Development
- Testing
- Launch
- Ensure smooth execution of sprints and releases
6. AI/ML Model Integration & Oversight
- Work with teams to integrate models into products
- Define requirements for:
- training data
- model evaluation
- deployment
- Monitor model performance in production
7. Responsible AI & Governance
- Ensure ethical and compliant AI usage:
- bias mitigation
- explainability
- privacy
- Align with regulations and internal policies
8. Product Performance & Optimization
- Continuously improve product based on:
- user feedback
- analytics
- A/B testing
- Optimize accuracy, usability, and business outcomes
9. Customer & Market Research
- Understand customer pain points and market trends
- Conduct interviews, surveys, and competitive analysis
- Translate insights into product features
10. Go-To-Market Strategy
- Define launch strategy:
- pricing
- positioning
- messaging
- Work with sales and marketing teams for successful rollout
11. Stakeholder Communication
- Present product vision, roadmap, and progress to executives
- Communicate trade-offs, risks, and outcomes clearly
12. Agile & Product Execution
- Lead Agile ceremonies:
- backlog grooming
- sprint planning
- retrospectives
- Ensure timely delivery of features