Product and Program Lead: AI Automation Solutions - Consultant

Description

Please note this position is remote globally - preferred time overlap with US time zones Background

Description Background Barely enough is not enough for anyone. Prosper Global is a humanitarian organization working alongside communities facing conflict, climate change, and economic hardship to meet urgent needs and create the conditions for lasting progress. Today's challenges demand new solutions, so we pair local knowledge with global resources to help communities build what's needed, test what's possible, and scale what's proven so that people everywhere can pursue a full life on their own terms. In 2026, we changed our name from Mercy Corps to Prosper Global, to reflect our belief that when every community can prosper, all of humanity moves forward. The Award Agreement Review Checklist (AARC) is Prosper Global's documented process for reviewing donor agreements before signature. Reviewers examine agreements and supporting documents, identify provisions relevant to each review question, record where supporting information appears, and develop an appropriate response based on technical judgment. This work is essential but requires repeated searching across lengthy documents, transferring information into the review record, and distinguishing routine information gathering from issues requiring expert analysis. This consultancy will support the validation, design, development, and pilot of an AI-enabled product to improve this workflow. AI tools should assist with locating, organizing, and summarizing relevant information and preparing draft inputs where appropriate. Reviewers will remain responsible for validating evidence, applying professional judgment, resolving ambiguity, and approving the final review record. The assignment will preserve human oversight and remain flexible about the interface and technical form of the product until user needs and business requirements are validated. Purpose / Project Description The purpose of this consultancy is to lead the validation, design, development, and pilot of an AI-enabled AARC product that reduces manual information gathering, supports completion of the review template, and helps prepare appropriate donor-facing responses while strengthening consistency, traceability, and effective use of reviewer expertise. The consultant will serve as Product and Program Lead for a business-led initiative sponsored by Operations Management. The consultant will coordinate directly with business stakeholders and engage IT, Technology for Development (T4D), Data Services, and other technical actors at defined points where their input, review, access, or specialist support is required. The delivery approach must not depend on sustained technical‑team capacity and should focus technical participation on essential decisions, safeguards, integration considerations, and handover requirements. Total estimated level of effort: approximately 3 months, with delivery targeted by late Dec 2026/early Jan 2027. Consultant Objectives

• Validate and refine the existing AARC problem statements, user needs, and business requirements through a time‑boxed validation sprint.
• Design a practical, user‑centered AI‑enabled product that assists reviewers with locating relevant agreement provisions, organizing supporting evidence, and preparing draft review inputs and donor responses for human validation and refinement.
• Deliver a tested pilot through iterative validation, prototyping, sandbox testing, and live‑use testing.
• Define and apply appropriate safeguards for accuracy, data protection, responsible AI use, and human review.
• Develop the essential product, technical, user, testing, and performance documentation needed for adoption and ongoing management.
• Provide a clear, evidence‑based recommendation for rollout, maintenance, and any future scaling of the AARC product.

Consultant Activities

• Problem and solution validation
• Begin with the existing proof‑of‑concept specification, stakeholder mapping, and available AARC process documentation rather than initiating open‑ended discovery.
• Conduct limited stakeholder interviews and structured validation sessions with the groups already identified in the stakeholder mapping.
• Confirm primary pain points, business requirements, priority use cases, and acceptance criteria.
• Confirm which AARC review questions may be supported by AI and which require direct human analysis, judgment, or approval‑only review.
• Solution design and planning
• Develop the solution design and delivery approach under the direction of the business owner, engaging technical teams at defined decision and review points.
• Define functional and non‑functional requirements, the division of work between reviewers and AI tools, user journeys, and essential solution‑architecture inputs.
• Develop a phased implementation plan covering prototype, sandbox, pilot, and rollout readiness.
• Design the approach so delivery can proceed within the required timeframe without assuming sustained capacity from IT, T4D, Data Services, or other technical teams.
• Success measures and risk management
• Define success measures, performance thresholds, critical failure conditions, and pilot‑entry criteria.
• Identify product, operational, data‑handling, accuracy, and responsible‑AI risks and define proportionate mitigation measures.
• Track pilot outcomes and prepare an indicative assessment of efficiency gains and potential value using evidence available from the pilot.
• Project planning and coordination
• Develop and maintain the detailed workplan, timeline, dependencies, and level‑of‑effort estimates.
• Prepare a focused stakeholder engagement plan and responsibility matrix that reflects business ownership and targeted technical participation.
• Coordinate business contributors and secure timely input from technology actors where required.
• Development, testing, and pilot delivery
• Lead development of the initial prototype and manage iterative refinement against agreed acceptance criteria.
• Develop and implement a test plan covering priority use cases, accuracy, completeness, usability, critical failure conditions, data handling, and agreed acceptance criteria for pilot entry.
• Coordinate sandbox and pilot testing with users.
• Assess pilot performance against agreed accuracy, usability, efficiency, and risk thresholds.
• Gather feedback, maintain an issue and improvement log, and drive prioritized refinements.
• Documentation, handover, and recommendations
• Develop concise user guidance and handover notes sufficient for internal owners to operate, assess, and govern the pilot after the engagement
• Maintain a decision and open‑issues log covering technical, governance, data, and support items requiring internal ownership after the engagement.
• Assess performance, document lessons learned, and recommend whether and how the product should proceed to rollout or further refinement.

Consultant Deliverables

• 1. Validation and requirements package
• Problem‑validation summary, confirmed priority use cases, business requirements, and defined scope of AI assistance.
• Initial success measures, performance thresholds, acceptance criteria, and product risk assessment.
• 2. Solution design and delivery plan
• Solution design documentation, including user journeys, functional and non‑functional requirements, division of work between reviewers and AI tools, and essential architecture inputs.
• Detailed workplan, timeline, dependency and level‑of‑effort estimates, stakeholder engagement plan, and responsibility matrix.
• Staged implementation plan covering prototype, sandbox, pilot, and rollout readiness.
• 3. Prototype, testing, and pilot package
• Working prototype and documented iteration history.
• Test plan and quality‑assurance approach, including human validation of AI outputs and defined critical failure conditions.
• Pilot plan, execution summary, issue log, and improvement log.
• 4. Governance handover package
• Essential user guidance and recommendations for training materials.
• Practical handover notes sufficient for designated internal owners to operate, monitor, and govern the pilot
• 5. Performance assessment and recommendation
• Pilot performance assessment covering agreed measures such as accuracy, completeness, usability, review‑time reduction, and risk thresholds.
• Indicative assessment of efficiency gains and potential value based on available pilot evidence.
• Executive summary and presentation materials with a recommendation for rollout, maintenance, further refinement, and any future scaling.

Timeframe / Schedule The final schedule and due dates will be confirmed at contracting. The engagement is expected to target completion within 12 weeks, with limited contingency negotiable if required. Activities may overlap or iterate where this supports timely delivery, provided core milestones and decision points remain clear. Target timing Primary focus Expected outputs Week 1 Kickoff and validation launch Project kickoff; confirmation of scope, working assumptions, available materials, stakeholder map, priority use cases, validation plan, and immediate information needs. Materials may be shared earlier after NDA execution, but pre‑kickoff review is not expected outside the engagement. Weeks 2-3 Requirements, safeguards, and test‑data preparation Validated user needs, business requirements, acceptance criteria, AI‑support boundaries, initial safeguards, pilot‑entry criteria, and test‑data preparation. Technical teams are engaged at defined review or decision points. Weeks 3-6 Solution design and initial prototype development Solution design, user journeys, functional and non‑functional requirements, delivery plan, and initial prototype build. Prototype development may begin while AI workflow validation continues, provided assumptions and risks are documented. Weeks 6-8 Sandbox testing and refinement Sandbox testing against prepared AARC cases, accuracy and usability review, issue and improvement log, prioritized refinements, and readiness check for pilot launch. Weeks 8-10 Pilot execution and iteration Pilot launch is targeted for Week 8, with Week 9 as the latest acceptable start if dependencies require it. Pilot delivery includes live‑use testing, performance tracking, user feedback, risk monitoring, and prioritized refinement. Weeks 11-12 Assessment, handover, and recommendation Pilot performance assessment, user guidance, product and technical handover documentation, lessons learned, executive materials, and recommendation for rollout, maintenance, further refinement, or future scaling. Weeks 12+ Managed contingency Reserved for limited dependency‑related delays, additional refinement, documentation completion, or final decision support. Use of this window should be agreed with the project sponsor. The Consultant Will Report to Senior Director, Operations Management The Consultant Will Work Closely With

• Donor Compliance Team
• IT Engineering and Data Services Teams
• Award Management Team and other AARC business owners and reviewers
• Data protection, information security, procurement, and other specialist functions where required
• Finance, Legal, and Country Teams, as needed
• Technology for Development (T4D), as needed

Required Experience And Skills

• 5-10 years of experience in a relevant technical, product‑management, digital‑delivery, or program‑delivery field (required).
• Strong product‑management and program‑delivery experience, including ownership of delivery from requirements validation through pilot and handover.
• Demonstrated experience leading AI, automation, or data‑enabled initiatives.
• Experience translating business processes and user needs into practical product requirements and delivery decisions.
• Experience managing pilots, iterative development, user testing, quality assurance, and acceptance criteria.
• Ability to work independently in a business‑led delivery model while engaging technical specialists efficiently at defined decision points.
• Familiarity with AI accuracy, data protection, information security, assurance, auditability, and responsible‑use risks.
• Strong stakeholder facilitation, documentation, and executive communication skills.

Team Engagement and Effectiveness Achieving our mission starts with how we build our team and collaborate. By bringing together individuals with a variety of experiences, backgrounds, and perspectives, we strengthen our ability to solve complex challenges and drive innovation. We foster a culture of trust and respect, where every team member is valued for their contributions, empowered to reach their full potential, and motivated to do our best work. We recognize that building a strong and effective team is an ongoing process, and we remain committed to learning, improving, and growing together. Equal Employment Opportunity Prosper Global is an equal opportunity employer committed to providing equal employment opportunities to all employees and qualified applicants for employment without regard to race, color, sex, sexual orientation, religion or belief, national origin, age, disability, marital status, veteran status, or any other characteristics protected under applicable law. Safeguarding and Ethics Prosper Global is committed to ensuring that all individuals we come into contact with through our work, whether team members, community members, program participants or others, are treated with respect and dignity. We are committed to the core principles regarding prevention of sexual exploitation and abuse laid out by the UN Secretary General and IASC and have signed on to the Interagency Misconduct Disclosure Scheme. We will not tolerate child abuse, sexual exploitation, abuse, or harassment by or of our team members. As part of our commitment to a safe and inclusive work environment, team members are expected to conduct themselves in a professional manner, respect local laws and customs, and adhere to Prosper Global Code of Conduct Policies and values at all times. Team members are required to complete mandatory Code of Conduct e‑learning courses upon hire and on an annual basis. #J-18808-Ljbffr