The Project Manager will provide strategic, technical, and operational leadership across mDoc’s AI-enabled phygital health initiatives, taking end-to-end ownership of project design, execution, and outcomes. This role requires deep technical fluency, analytical rigor, and the ability to rapidly develop subject-matter expertise across AI/ML, digital health architecture, product development, data systems, business systems and maternal health system implementation. You will be expected to critically interrogate technical approaches, challenge assumptions, anticipate risks and dependencies, and drive evidence-informed decisions—not simply coordinate activities and timelines. Working across multidisciplinary technical, clinical, product, and implementation teams, as well as external partners and government stakeholders, you will translate complex technical and contextual requirements into scalable, interoperable, safe, and high-impact AI-enabled self-care solutions across Nigeria. We are looking for a technically sophisticated leader who can interrogate the work, challenge technical decisions, anticipate implementation risks, and drive execution with a clear focus on ownership. mDoc still functions as a startup and is looking specifically for people who thrive in such environments and who can create systems when there is chaos. Working across engineering, AI/ML, product, clinical, research, and implementation teams, as well as external technology partners and health system stakeholders, you will lead the execution of integrated, scalable, safe, and contextually appropriate AI-enabled health solutions. You will also ensure that technical decisions, innovations, and implementation lessons strengthen mDoc's broader technology ecosystem, promote reuse of existing capabilities, and prevent unnecessary duplication or fragmentation across initiatives. This is not a project or technical coordination role. We are looking for a technically sophisticated, analytically rigorous project leader who takes ownership of understanding the substance of the work, who is curious, who can understand complex systems, challenge specialists constructively, drive integration, and take accountability for exceptional delivery. Key Responsibilities 1. Technical Leadership and Subject-Matter Mastery ● Develop deep working knowledge of reproductive and maternal health, self-care, coaching, the architecture, AI/ML systems, software platforms, data infrastructure, APIs, interoperability requirements, and technical workflows underpinning assigned initiatives. ● Independently research and rapidly master unfamiliar technologies, technical approaches, evaluation methods, and emerging industry developments. ● Engage substantively with cross-functional teams and consultants to understand and critically evaluate technical decisions. ● Interrogate assumptions, assess feasibility, identify design weaknesses, and challenge teams to develop more effective, reliable, scalable, and sustainable solutions. ● Maintain a high standard of curiosity, continuous learning, and intellectual ownership. 2. End-to-End Project Leadership and Execution ● Take full accountability for project delivery against agreed scope, timelines, budgets, quality standards, and intended outcomes. ● Translate strategic objectives, technical requirements, and implementation constraints into integrated execution plans, technical milestones, dependencies, deliverables, and accountability structures. ● Maintain clear project governance, including project charters, master decks, roadmaps, critical paths, risk registers, decision logs, and performance dashboards. ● Identify and proactively manage internal and external dependencies across workstreams, manage team, consultants as well as broader external stakeholders including government and consortium partners. ● Evaluate trade-offs across technical feasibility, architecture, performance, safety, cost, scope, and timelines. ● Drive timely decisions, disciplined execution, and accountability across teams. ● Escalate complex issues with evidence-based analysis and clear options 3. AI/ML and Advanced Digital Health Implementation ● Oversee technical implementation across cross-functional workstreams owned by product, engineering, ML, data, research, clinical and coaching, growth. ● Understand the AI development lifecycle, including data preparation, model development, evaluation, deployment, monitoring, and continuous improvement. ● Work with AI/ML, engineering, product, data, research and clinical teams to establish clear functional requirements, technical specifications, acceptance criteria, and evaluation plans. ● Understand and manage dependencies between internal and external systems and drive implementation planning accordingly. ● Work with R & L and Product teams to coordinate technical testing and optimization across different languages, user groups, devices, and connectivity environments. ● Identify risks associated with model limitations, data quality, integration failures, version changes, and performance degradation. ● Support responsible AI implementation through appropriate governance, human oversight, monitoring, and escalation mechanisms. 4. Systems Architecture, Integration, and Interoperability ● Lead coordination of technical integration and proactively identify architectural dependencies, integration risks, interface requirements, and technical trade-offs. ● Work with teams and partners to define and manage requirements for APIs, standards-based data exchange, interoperability, and secure information flows. ● Coordinate integration with frontline health worker systems, facility-based digital platforms, and clinical decision-support tools where applicable. ● Ensure integration requirements consider shared and standard-based data exchange, aligned clinical logic, referral and follow-up workflows, and bidirectional information sharing where feasible. ● Promote architecture and integration decisions that support reliability, maintainability, scalability, and long-term organizational value. 5. Clinical Safety, Responsible AI, and Quality Assurance ● Ensure project plans incorporate best-in-class clinical safety, privacy, security, reliability, and responsible AI requirements. ● Coordinate with clinical and technical leads to harness mDoc monitoring and evaluation methods. ● Work with technical teams to establish measurable acceptance criteria, test plans, release-readiness requirements, monitoring mechanisms and communication. Support monitoring and continuous improvement following deployment, including identification of emerging risks, model drift, and user-reported issues. 6. Cross-Project Technical Integration and Organizational Learning ● Proactively identify opportunities for shared projects, architecture, reusable AI/ML components, common data infrastructure, evaluation frameworks, and interoperable workflows. ● Work across project and functional teams to align technical priorities, identify dependencies, and coordinate development efforts. ● Challenge siloed technical decisions that create duplication, fragmentation, technical debt, or barriers to long-term scalability. ● Facilitate cross-project technical reviews, knowledge sharing, and coordinated problem-solving. ● Ensure innovations, technical assets, documentation, and implementation lessons are captured and made available for organizational reuse. 7. Analytical Rigor and Technical Problem-Solving ● Critically evaluate designs, documentation, MOUs, consultant deliverables, monitoring and evaluation results, implementation data, and team outputs. ● Use quantitative and qualitative evidence to diagnose underperformance, identify root causes, and recommend corrective actions. ● Challenge unsupported assumptions, superficial explanations, and incomplete technical recommendations. ● Develop clear, evidence-based recommendations that consider alternative approaches, technical constraints, risks, and trade-offs. ● Take intellectual ownership of complex problems rather than automatically deferring technical matters to specialists. 8. Cross-Functional Leadership and Stakeholder Management ● Lead multidisciplinary teams spanning engineering, AI/ML, product, clinical operations, research, implementation, and partnerships. ● Facilitate technically substantive discussions that result in clear decisions, ownership, and action. ● Manage dependencies and competing priorities across internal and external teams while maintaining strong communication and accountability, 9. Performance Monitoring and Continuous Improvement ● Define and monitor indicators covering technical delivery, integration quality, system performance, adoption, safety, implementation effectiveness, and intended outcomes. ● Monitor defects, integration failures, user feedback, and emerging implementation risks. Ensure lessons from testing, deployments, evaluations, and user experiences inform future technical and operational decisions. ● Develop clear technical project documentation, implementation playbooks, and knowledge-transfer materials. 10. Value Creation ● Develop a strong understanding of member segments, value proposition, cost structure, and long-term sustainability and scalability strategy. ● Evaluate project decisions through both an impact and sustainability lens, considering cost-effectiveness, unit economics, operational efficiency, scalability, and potential for cost recovery. ● Demonstrate financial ownership beyond budget tracking by understanding key cost drivers, identifying inefficiencies, evaluating return on investment, and recommending opportunities to optimize resource allocation. ● Apply customer-centric and market-oriented thinking, ensuring that solutions address real user and customer needs, deliver a differentiated value proposition, and create measurable value for members, partners, payers, and other stakeholders. ● Understand the relationship between project outputs, user adoption, engagement, retention, health outcomes, customer satisfaction, and organizational sustainability. ● Contribute to use cases, financial analyses, investment prioritization, and strategic recommendations that inform project and organizational decision-making. About You Required Qualifications ● Bachelor's and Master's degrees from recognized universities, with a strong record of academic achievement, preferably First Class Honours or Second Class Upper (2:1), or equivalent. ● Approximately 4 - 7 years of relevant professional experience managing complex, multidisciplinary projects, preferably in technology, healthcare, management consulting, startups, or commercially oriented organizations. ● Strong professional track record, with evidence of intellectual curiosity, initiative, leadership, and exceptional performance. ● Demonstrated excellence in analytical and quantitative reasoning, structured problem-solving, and critical thinking. ● Demonstrated ability to rapidly develop subject-matter expertise and engage substantively with technical or specialized work. ● Strong business acumen, including the ability to interpret financial information, evaluate cost drivers, and make sound resource-allocation decisions. ● Excellent project planning, execution, risk management, and communication skills. ● Experience working in dynamic, resource-constrained, or rapidly evolving environments. Practical experience using digital and Generative AI tools or technologies to improve workflows, automation, analytics, or data platform capabilities ● Familiarity with agile methodologies and project management platforms. Bonus Points for: ● Direct experience managing AI, LLM, or Machine Learning deployments in low-resource settings. ● Hands-on experience with health information systems, FHIR standards, or national/state digital health platforms (e.g., DHIS2, eCHIS). ● Mastery of Agile, Scrum, or hybrid project management methodologies in fast-paced product environments. Why Join Us At mDoc, you'll help shape the future of AI-enabled self-care in Africa and beyond while tackling complex challenges at the intersection of technology, business, and health. You'll work alongside a multidisciplinary, mission-driven team, take ownership of meaningful initiatives, and have opportunities to grow your technical, analytical, commercial, and leadership capabilities. We offer a dynamic, entrepreneurial environment where curiosity is encouraged, innovation is valued, and your work can create measurable impact at scale. How to Apply You should include these in your application: ● A resume ● A cover letter. Your application will not be reviewed otherwise. We take the process of hiring very seriously and as such you will be asked to undergo a behavioural and technical assessment of your skills before moving forward in the process. Only short-listed candidates will be notified if they are moving ahead in the process. Please send applications to [email protected] Learn more at www.mymdoc.com.