AI & Data Product Manager/Owner

We are seeking
a highly experienced AI & Data Product Manager to lead the strategy,
development, and delivery of cutting -edge AI - and data -driven products. This
role sits at the intersection of business, data science, and engineering,
owning the end -to -end lifecycle of AI/ML products while ensuring ethical,
scalable, and value -driven outcomes.

Key
Responsibilities

·       Define,
own, and execute the product vision, roadmap, and strategy for AI & data
products

·       Translate
business objectives into clear Product Requirement Documents (PRDs) and user
stories

·       Prioritize
features, use cases, and backlogs based on business value, feasibility, and
risk

·       Lead
cross -functional collaboration with Data Science, Engineering, UX, and Business
teams

·       Manage
the full AI/ML lifecycle: development, deployment, monitoring, retraining, and
optimization

·       Ensure
Responsible AI practices including fairness, transparency, governance, and
compliance

·       Define
and track product KPIs, success metrics, and business outcomes

·       Oversee
data quality, governance, integration, and analytics platforms

·       Drive
stakeholder alignment, executive communication, and product evangelism

·       Coordinate
A/B testing, experimentation, and continuous improvement initiatives

·       Ensure
security, privacy, and regulatory compliance (e.g., POPIA and global standards)

·       Lead
documentation, user enablement, training, and adoption initiatives

Requirements

Must -Have
Skills & Competencies

·       Strong
understanding of AI/ML concepts, data pipelines, and analytics platforms

·       Hands -on
experience with SQL, Python, and cloud platforms (AWS / Azure / GCP)

·       Proven
Product Management expertise using Agile / Scrum methodologies

·       Experience
writing PRDs, managing backlogs, and owning roadmaps

·       Strong
stakeholder management, communication, and leadership skills

·       Familiarity
with MLOps, model monitoring, version control, and deployment practices

Good -to -Have
Skills

·       Experience
with Kubernetes, Docker, and scalable architectures

·       Exposure
to Ruby on Rails and/or Java

·       Knowledge
of NVIDIA H200 GPU environments or high -performance AI infrastructure

·       Experience
in Business Analytics or Business Administration

·       MBA,
Computer Science, AI, or related advanced qualification

Screening
Focus – Must -Have Validation

·       Hands -on
experience managing AI/ML product lifecycles

·       Proven
ability to translate business problems into AI/data solutions

·       Strong
experience in cloud -based data and AI platforms

·       Demonstrated
stakeholder management at senior/executive level