Product Owner
Purpose
To own the definition and delivery of MIE's digital platform products - translating business and customer need into clear, testable requirements, and holding the backlog, delivery cadence and release quality that turn those requirements into working software.
The Product Owner is the single point of accountability for what the delivery team builds and in what order. The role sits between the business and engineering: close enough to the commercial agenda to prioritise correctly, and close enough to the build to be trusted by the people doing it.
About the role
MIE is building a new enterprise platform for human capital intelligence, moving to a single scalable foundation capable of carrying a broader and more diverse set of AI-enabled solutions for employers, candidates and partners. This is a delivery-focused Product Owner role: you will own a defined product area across the delivery lifecycle - requirements, backlog, delivery cadence, acceptance testing and release - and you will be expected to be AI-fluent in practice, using AI tooling in your own workflow and building working prototypes yourself rather than commissioning them. You will contribute to pricing, packaging and go-to-market decisions with evidence from usage data.
Key responsibilities
Requirements definition and user stories
● Elicit business and customer requirements through structured engagement with stakeholders, users and subject-matter experts.
● Translate requirements into user stories with clear, testable acceptance criteria that a developer and a tester can both work from without further clarification.
● Raise ambiguities, dependencies and gaps early, rather than resolving them by assumption.
● Maintain traceability from business need through to delivered functionality.
AI fluency and rapid prototyping
● Use AI tooling routinely across the product workflow - research synthesis, requirements drafting, test-case generation and data interrogation - while retaining personal accountability for the accuracy of any output that carries your name.
● Build clickable, working prototypes independently to test concepts with stakeholders and users, replacing static specifications with something people can use before engineering effort is committed.
● Distinguish clearly between a prototype and a production candidate, and make that distinction explicit at handover to engineering.
● Apply MIE's information-security and POPIA obligations to the use of AI tooling, including a working judgement on what data may not be submitted to third-party models.
Backlog ownership and prioritisation
● Own and maintain the product backlog for the assigned product area, keeping it refined, estimated and ready for delivery.
● Prioritise against business value, dependency and risk, and defend the sequencing to both engineering and the business.
● Break large scope into releasable increments that deliver value early.
● Manage scope change through a transparent process, with the trade-off made explicit rather than absorbed silently.
Agile delivery execution
● Run the delivery cadence for the product area - refinement, sprint planning, stand-ups, reviews and retrospectives.
● Work day to day with engineering, design and quality assurance as the decision-maker on requirement intent.
● Track delivery against commitments, and escalate slippage with a proposed course of action rather than a status update.
● Contribute to continuous improvement of how the team works, not only of what it builds.
Testing, quality and releases
● Write test cases from acceptance criteria and coordinate user acceptance testing with business users.
● Triage and track defects through to resolution, with a defensible view of severity and priority.
● Own release readiness for the product area: release notes, go / no-go input and post-release verification.
● Support post-release stabilisation, feeding defects and user friction back into the backlog.
● Define and maintain evaluation datasets and quality thresholds for AI-enabled features, and own regression testing across model changes as well as code changes.
● Specify where human review remains mandatory, and define the escalation rules for low-confidence or contested system outputs.
Product performance and data insight
● Define and monitor the measures that show whether the product is working - adoption, usage, throughput, error and abandonment rates.
● Interrogate usage and performance data directly, and report findings with a recommendation attached.
● Identify product gaps and improvement opportunities from evidence rather than anecdote.
● Contribute research on customer need, competitor capability and market expectation to inform roadmap decisions.
Stakeholder management and collaboration
● Build working relationships across operations, commercial, compliance, service delivery and engineering.
● Represent the product area credibly to senior stakeholders, including at executive forums.
● Manage competing stakeholder demands transparently, keeping decisions and their rationale visible.
● Work effectively in a matrix environment, where influence rather than authority secures cooperation.
Documentation and written precision
● Produce and maintain product documentation: requirements specifications, process flows, test cases, release notes and user guides.
● Write to a standard where the reader can act without needing to ask a follow-up question.
● Keep documentation current as the product changes, so that it remains a working reference rather than a historical record.
Commercial and customer enablement
● Support sales and client teams with product demonstrations, solution walkthroughs and product content for bids and tenders.
● Contribute input to pricing, packaging and positioning decisions, grounded in usage data, delivery cost and customer feedback.
● Support customer onboarding and adoption, including training and enablement material.
Confidentiality, compliance and governance
● Treat information as confidential by default - personal data, commercial terms, product plans, and information belonging to clients or third parties.
● Ensure that product decisions and delivered functionality comply with POPIA and with MIE's governance, quality and information-security standards.
● Build compliance and auditability into requirements from the outset, rather than retrofitting them later.
What you'll bring
● Demonstrated experience owning a product backlog and writing requirements that a delivery team has successfully built from.
● Practical fluency in agile delivery - you have run the ceremonies, not only attended them.
● Hands-on experience of acceptance testing and release management, including defect triage and release readiness.
● Strong analytical capability, with the confidence to work directly with usage and performance data and to form a view from it.
● Demonstrated use of AI tooling in product work, and the ability to build a working prototype without engineering support.
● Judgement about when AI output can be relied upon and when it must be verified by a person - and the ability to set that threshold from tested error rates rather than assumption, particularly where personal information is involved.
● Precise, structured writing. Much of the output of this role is a document that someone else must be able to act on.
● Credible communication with senior stakeholders, and the ability to hold a position under challenge without becoming rigid.
● Sufficient technical grounding to hold a substantive conversation with engineers about feasibility, effort and trade-off.
● The judgement to operate in a regulated environment, where confidentiality and compliance are conditions of the work rather than constraints on it.
Qualifications and experience
● A relevant tertiary qualification (Commerce, Information Systems, Business Analysis, Industrial Engineering or related).
● Five or more years' experience in product ownership, business analysis or product delivery.
● Advantageous: a recognised product ownership or business analysis certification; exposure to human capital technology, financial services or another regulated environment; working knowledge of SQL; hands-on use of AI prototyping tools.
Personal attributes
● Meticulous. Precision is the core deliverable of this role, not a refinement of it.
● Organised under competing deadlines, and resilient in an environment where requirements change.
● Coachable and self-aware, with the habit of seeking feedback rather than waiting for it.
● Decisive - able to make a call on incomplete information and to revisit it when better information arrives.
● Ethical and discreet with confidential information of every kind.
Work Location: In person
