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ShyftLabs
Artificial Intelligence & Machine Learning Services
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ShyftLabs is seeking a client-facing Data & AI Product Manager to support a Quality AI initiative for a leading enterprise client. In this role, you will work as an extension of the client's Data & Analytics (D&A) team, partnering closely with Quality business stakeholders, technology teams, and implementation vendors to drive the successful delivery of AI-powered solutions.
This is a hands-on product management opportunity for someone who can bridge business needs and technical execution, translate complex requirements into actionable product deliverables, and ensure that solutions deliver measurable business value. You will play a key role in providing product oversight, challenging vendor recommendations, coordinating implementation activities, and ensuring AI-driven workflows are reliable, user-friendly, and aligned with business objectives.
The ideal candidate combines strong stakeholder management and delivery coordination skills with an understanding of enterprise data, analytics, and emerging AI capabilities. You should be comfortable engaging directly with senior stakeholders, facilitating cross-functional discussions, and driving accountability in a complex enterprise environment.
Serve as a key product management partner to the client's Data & Analytics team, acting as the bridge between Quality business stakeholders, IT, data teams, and external implementation vendors.
Facilitate stakeholder discussions and requirements-gathering sessions to understand business needs, define priorities, and translate requirements into actionable product deliverables.
Manage day-to-day coordination across business and technical teams, ensuring alignment on scope, timelines, dependencies, deliverables, and implementation priorities.
Communicate product progress, risks, decisions, and recommendations clearly to business stakeholders and leadership.
Constructively challenge assumptions, proposed solutions, and vendor deliverables to ensure they meet business requirements and enterprise standards.
Review and evaluate vendor deliverables, including solution architectures, AI workflows, user interfaces, data mappings, testing strategies, and implementation plans.
Assess proposed AI-enabled solutions to ensure they address business requirements, support effective human oversight, and provide appropriate transparency into findings, exceptions, and recommendations.
Partner with business and technology teams to shape user-facing interfaces that enable Quality stakeholders to review documentation, investigate findings, assess exceptions, evaluate AI-generated recommendations, and support release decisions.
Coordinate business validation, user acceptance testing (UAT), defect resolution, and launch readiness activities.
Track implementation risks, dependencies, open issues, and decisions to maintain delivery momentum and ensure timely resolution.
Support the transition from implementation to operational use, ensuring stakeholders are prepared to adopt and effectively use the solution.
Define, challenge, and refine key performance indicators (KPIs) to measure the effectiveness and business impact of the Quality AI initiative.
Partner with the Value team to establish appropriate measurement frameworks, validate assumptions, and ensure benefits are tracked against agreed business objectives.
Translate business objectives into measurable product outcomes, ensuring the solution delivers tangible improvements in efficiency, quality, consistency, and decision-making.
Collaborate with data and analytics teams to validate data requirements, mappings, reporting needs, and the quality of information supporting AI-enabled workflows.
Maintain clear documentation of product requirements, decisions, risks, dependencies, action items, and delivery status.
4–8 years of experience in product management, data and analytics, business analysis, digital transformation, or a related field.
Demonstrated experience supporting the delivery of enterprise data, analytics, AI, or digital products from requirements definition through implementation and launch.
Strong client-facing experience, with the ability to build trusted relationships and coordinate effectively across business stakeholders, technical teams, and external vendors.
Experience reviewing technical deliverables, challenging proposed solutions, identifying gaps, and driving alignment between business expectations and technical implementation.
Familiarity with Generative AI, document intelligence, optical character recognition (OCR), AI agents, or human-in-the-loop workflows.
Strong communication, facilitation, presentation, and stakeholder management skills, including the ability to navigate competing priorities and constructively challenge demanding stakeholders.
Experience coordinating UAT, business validation, issue resolution, and implementation readiness.
Ability to define success metrics, evaluate product performance, and connect delivery outcomes to measurable business value.
Strong organizational skills, attention to detail, and the ability to manage multiple workstreams in a fast-paced enterprise environment.
Comfortable working independently while maintaining strong alignment with client stakeholders and cross-functional delivery teams.
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