Cross-Platform Mobile Application Developer (Consultant) - Hybrid

Established in 2003, Malaria Consortium is one of the world’s leading non-profit organisations specialising in the prevention, control and treatment of malaria and other communicable diseases among vulnerable populations. Our mission is to save lives and improve health in Africa and Asia, through evidence-based programmes that combat targeted diseases and promote universal health coverage.

We are recruiting to fill the position below:

Job Title: Cross-Platform Mobile Application Developer (Consultant)

Location: Abuja (FCT) 
Employment Type: Hybrid

Objective of the Assignment

• The overall objective is to engage a highly experienced cross-platform mobile application consultant with demonstrated expertise in Artificial Intelligence integration to:
  • Provide comprehensive management and administrative portals.
  • Design and develop a secure mobile learning platform for Android and iOS.
  • Develop an AI-powered assistant based on approved SARMAAN II knowledge sources.
  • Deploy, train administrators, and provide post-implementation support.
  • Enable offline learning and synchronization.
  • Deliver scalable analytics and reporting capabilities.
  • Ensure compliance with data privacy and security standards.
  • Build multilingual training and assessment capabilities.

Scope of Work

• These should include API services, authentication services, learning management services, AI services, data storage, an analytics engine, a notification engine, Retrieval-Augmented Generation (RAG), knowledge indexing, an AI assistant, AI governance controls, AI analytics and monitoring, and translation support.
• The platform architecture should incorporate services and functionalities for user administration, content management, assessment configuration, AI governance, reporting, and monitoring.
• The application must support Android and iOS devices, low-bandwidth environments, offline-first architecture, and synchronization services to ensure seamless access and data synchronization.
• The selected developer is responsible for the design, development, and deploying a platform architecture for an application to be hosted on the Google Play Store and Apple App Store.

Deliverables

Ref.

Deliverable

Number of days

Minimum Contents

D1

Inception report and requirements baseline

3

Confirmed user groups, workflows, learning pathways, requirements traceability matrix, dependencies, risk assessment, integration assessment, acceptance criteria and approved work plan.

D2

Solution architecture and technical design

5

Architecture diagrams, technology stack, data model, security/privacy design, environment plan, deployment approach, scalability assumptions and recurring cost estimates.

D3

UI/UX designs and prototypes

5

Reviewed user journeys and clickable prototypes for mobile and web interfaces, including feedback from representative users.

D4

Functional/technical specifications and test plan

5

Functional and non-functional specifications, API documentation, data dictionary, requirements traceability and quality assurance/test plan.

D5

Development and test environments

5

Configured development and test/staging environments, repository access, build/deployment process and access controls.

D6

Core mobile application and backend services

5

Working mobile application, authentication, user roles, learning dashboard, core workflows, backend, database and documented APIs.

D7

Learning management portal and content management system

4

User administration, content workflows, learning pathways, content versioning, assessment configuration, and AI knowledge-source administration.

D8

Assessment and certification functionality

4

Assessment of types, question banks, pass/retake rules, attempt records, remediation pathways and verifiable certificates.

D9

Offline functionality and synchronization

3

Offline content access and supported assessments, secure local storage, progress persistence, sync status, duplicate prevention, conflict handling and test evidence.

D10

AI-powered learning assistant and knowledge base

3

RAG over approved programme sources, source references, uncertainty handling, escalation, feedback, governance controls, logging and evaluation results.

D11

Analytics and reporting

3

Management dashboards, agreed indicators, downloadable data exports, scheduled reports and documented calculation definitions.

D12

System integration and end-to-end test report

4

Integration results, end-to-end test cases, test evidence, defect log and resolution status against approved requirements.

D13

Security, privacy, performance and recovery test reports

2

Security/privacy assessment, performance and concurrency results, backup/restore verification, recovery evidence and resolution or formal risk acceptance of findings.

D14

User acceptance testing and remediation

3

UAT plan, representative-user feedback, issue register, retest results, outstanding limitations and documented UAT sign-off.

D15

Production deployment and operational readiness

3

Production release, go-live checklist, monitoring, backup/recovery procedures, operational runbook and verification of production configuration.

D16

Training and knowledge transfer

2

End-user and administrator training, training materials, attendance/participation records and knowledge-transfer sessions for designated technical staff.

D17

Source-code and technical handover

2

Complete source-code repositories, deployment scripts, infrastructure/configuration assets, database schema, API documentation, dependency/licence inventory and transfer of access/ownership.

D18

Final report, warranty and support plan

2

Final delivery and acceptance status, known limitations, outstanding issues, cost summary, warranty terms, support/escalation arrangements and maintenance plan.

Total Number of Days

63 days

Required Qualifications and Experience
The consultant must demonstrate:

• Experience implementing multilingual solutions.
• Experience deploying cloud-based enterprise systems.
• Minimum of 3 years’ experience deploying AI-enabled solutions and similar applications to be built.
• Minimum of 5 years' experience in mobile application development.
• Proven experience delivering learning management platforms.
• Experience supporting offline-first applications.

Strong experience in:

• RESTful APIs
• Training and capacity building systems
• Cloud platforms (Azure, AWS or GCP)
• Flutter or React Native
• Android and iOS development
• Knowledge management systems
• AI governance frameworks
• AI/LLM integration
• Analytics and dashboard development
• Multilingual African language solutions.
• Health sector digital platforms
• Python, NET, Node.js, Java or equivalent backend technologies
• Retrieval Augmented Generation (RAG)
• Vector databases
• Data security and privacy compliance

Functional Requirements

• The system may also optionally support OTP authentication and configurable security policies to enhance security and access management.
• Users should be able to log in using their phone number or unique ID and authenticate using a password or PIN.
• The system should support user registration and authentication through role-based access control, allowing access to features and functionalities based on assigned user roles.

Privacy and Consent Management:

• The privacy notice must be available in English, Hausa, and Fulfulde. The system should record each user’s consent status, consent version, timestamp, and selected language for accountability and compliance purposes.
• The application must provide users with access to a privacy notice detailing the data collected, the purpose of data collection, the data retention period, data-sharing arrangements, and users’ rights.
• Where a user declines to provide consent, the system must prevent further access and redirect the user to the welcome page.

Multilingual Capability
The platform should provide:

• The platform will support English, Hausa, and Fulfulde language selection during onboarding, allow users to change their preferred language at any time through the settings menu, provide translation management functionality, deliver AI responses and notifications in the user's selected language, and maintain content version control across all supported languages to ensure consistency and accuracy.

Learning Management Features

• The dashboard should display:
  • Assigned learning path
  • Assessments
  • Certificates
  • Learning progress
  • Outstanding learning requirements
• Each training module should: Clearly define its objectives, outline the learning requirements and prerequisites, provide an estimated duration for completion, specify the minimum learning time required before a learner can progress or complete the course, and establish completion criteria that learners must meet to successfully finish the module and receive recognition or certification.
• The system should support role-based learning pathways for: CDD, OIC, HFW, Supervisors and additional cadres as may be configured
• Learning paths should include: Mandatory modules, Optional modules, Assessments and Certification requirements

Learning Content Delivery:

• Requirements: Low-bandwidth optimization
• Features: Play, Pause and Replay
• Features: Scroll, Read, Bookmark, Play , Pause and Replay
• Requirements: Optimized streaming, Download capability and Low-bandwidth versions

Learning Integrity Controls
The system should implement:

• Module-specific configuration of learning time requirements, track active learner engagement throughout the learning process, provide start, pause, and resume functionality for learning sessions, and enforce minimum learning time thresholds to ensure that learners cannot complete a module until the defined learning duration and engagement requirements have been met.

The system should:

• Present assessment questions throughout the learning experience to promote active participation, prevent passive or unattended course completion, capture and measure learner understanding, assess competency against defined learning outcomes, apply configurable pass marks to determine successful completion, and provide flexible, configurable retake options for learners who do not achieve the required score.

The platform should:

• Measure baseline knowledge and automatically score responses.

Where learners fail:

• Guessing behavior should be minimized.
• Reattempt policies must be enforced
• Relevant content must be revisited

Module completion should require:

• Content consumption completed
• Assessment criteria achieved.
• Knowledge checks completed 
• Minimum learning time met

Certificate Management:

• Store certificate records.
• Allow certificate download
• Automatically generate certificates

Recommended features:

• QR Code verification
• Certificate validation service.

Offline Learning Capability:

• Because deployment targets field personnel working in low-connectivity environments, offline capability is mandatory.

The application should:

• Enable learners to download approved learning content for offline use, access course materials without an internet connection, complete assessments while offline, and securely store assessment results locally on the device for synchronization with the central system once connectivity is restored.
• Offline data will be encrypted to protect sensitive information, secured against unauthorized access through appropriate authentication and device-level safeguards, and managed in a manner that prevents duplicate assessment submissions by validating and synchronizing records before they are submitted to the central system.

The system should:

• Allow manual sync
• Display last synchronization date/time.
• Sync automatically
• Resolve conflicts

AI Requirements:

• The proposed solution must include advanced AI functionality powered by secure Retrieval-Augmented Generation (RAG).
• The mobile application should provide: Conversational question-and-answer functionality, Learning support and Procedure guidance.

Requirements:

• No hallucinated content.
• Maximum question size configurable
• Grounded responses only

The solution will support:

• Voice-based questions and interactions in multiple languages, including English, Hausa, and Fulfulde, leveraging voice recognition capabilities to capture learner responses and provide audio-based assessment questions.
• The system will generate both text and audio responses where appropriate, use clear and simple language to improve understanding, and consistently respect each user's selected language preferences across all learning, assessment, and communication activities.
• This functionality is particularly designed to enhance accessibility and usability for low-literacy users and remote field workers who may have limited reading and writing proficiency.

RAG Knowledge Base

• Furthermore, the AI will support multilingual interactions and deliver clarifications in the user’s selected language while ensuring that all responses remain aligned with and constrained by approved training materials, thereby preserving the integrity, accuracy, and governance of official learning content.
• The AI will understand the learner’s current training module, deliver module-specific assistance, maintain contextual awareness throughout interactions, identify concepts that learners find challenging, simplify complex topics, and provide additional explanations tailored to the learner’s needs.
• The AI-powered learning assistant will provide document references, section references, and source citations for all guidance and responses, ensuring transparency, traceability, and user trust by clearly identifying the origin of information.
• The AI architecture should include only approved content should be indexed, including:
  • ePlaybooks
  • Approved programme documentation
  • FAQs
  • SOPs
  • Training manuals
  • The AI should never use unrestricted internet content when answering learner questions.

Where confidence levels are low:

• Escalate to Trainer
• Flag unresolved questions
• Escalate to Supervisor
• The AI should not fabricate information.

AI Feedback System:

• Learners should be able to rate AI responses.

Ratings should support:

• Analytics
• Knowledge gap analysis
• Continuous improvement

Administrators should be able to:

• Manage source documents
• Configure escalation rules.
• Configure AI behavior
• Define restricted topics

The platform should record: 

• Unanswered questions while enforcing privacy controls and retention rules.
• Questions submitted
• Feedback received
• Responses generated
• Escalations raised

Administrators should be able to: 

• Publish content
• Archive content
• Version control is mandatory.
• Upload new content
• The AI must index only approved content.
• Approve content

Management Portal Requirements

• Provide visibility into:
  • Completion rates
  • Programme performance
  • Pass rates
  • Retention rates 
  • Learning progress.
• The system should include a web-based management portal.

Capabilities should include:

• Update users
• Assign roles.
• Deactivate users
• Create users

Roles include:

• The system should implement least-privilege access principles.
• Learner
• Supervisor
• Administrator
• Trainer
• Management

The management portal should provide:

• Filters should include State, LGA, Facility and Role
• Supervisor performance analytics
• OIC performance analytics
• HFW performance analytics
• Track: Completed training, Pending training and Overdue training.
• CDD performance analytics

Monitor:

• Module progress
• Time spent
• Completion rates
• Learning trends

The solution should identify:

• Generate alerts.
• Unusually fast completion
• Repeated suspicious behavior

Provide:

• LGA-level reporting
• Using map and chart visualizations.
• State-level performance reporting
• Facility-level reporting

Monitor:

• Failure rates
• To identify weak content areas.
• Completion rates
• Scores

Content Management System (CMS):

• Learning content
• Documents
• AI knowledge sources.
• FAQs
• SOPs
• Modules

Capabilities should include:

• Review
• Approve
• Create
• Publish
• Archive
• Version control is mandatory.
• Edit

Assessment Management:

• Approval workflows.
• Question editing
• Question creation
• Test configuration

Question types may include:

• True/false
• Scenario-based questions
• Reporting Requirements: PDF , Excel and CSV
• Difficulty levels should be configurable.
• Matching
• Multiple choice

Filters should include:

• Role
• Support for scheduled automated reporting is required.
• LGA
• State
• Learning path
• Module
• Date

Notification Management:

• Notifications should support English, Hausa and Fulfulde languages.
• Retention assessment reminders
• Assessment alerts
• Reminders
• Push notifications
• Announcements

Security Requirements:

• MFA for management users
• Backup and recovery controls.
• Secure authentication
• Data encryption in transit
• Secure APIs
• Data encryption at rest
• Secure offline data storage
• Role-based access control
• Session management
• Audit logging

Infrastructure, Monitoring and Disaster Recovery:
The solution must provide:

• Recovery testing
• Uptime monitoring
• Storage monitoring
• Disaster recovery plan.
• Error monitoring
• API monitoring
• Scheduled backups

Developer should define:

• RTO (Recovery Time Objective).
• RPO (Recovery Point Objective)

Implementation Timeline:

• Development
• UX/UI design
• Go-live support.
• AI integration
• User acceptance testing
• Requirements validation
• Testing
• Training
• Deployment

Indicative Timeline:

• The schedule allows related workstreams to proceed in parallel where appropriate, while preserving adequate time for testing, remediation, approval, and handover.
• The selected provider should submit a detailed, dependency-aware implementation work plan covering requirements validation, solution architecture, UI/UX design, mobile and backend development, learning management functionality, offline synchronisation, AI integration, analytics, system integration, quality assurance, security testing, user acceptance testing, deployment, training and technical handover.
• The assignment should be implemented over an indicative period of Nine (9) weeks from the contract commencement date.

Period

Phase

Key outputs

Week 1

Inception and requirements validation

Stakeholder consultations, requirements baseline, integration assessment, risk assessment and acceptance matrix.

Week 2

Architecture, UI/UX and environment preparation

Architecture and technical design, prototypes, specifications, test plan and development/test environments.

Weeks 3–5

Core platform and backend development

Mobile application, backend/API services, authentication, learning workflows, and core data services.

Weeks 4–5

Learning management, content, assessment and certification

Management portal, CMS, learning pathways, assessment configuration, learner progress and certificates.

Weeks 4–6

Offline functionality and synchronisation

Offline learning and assessments, secure local storage, synchronisation, conflict handling, and offline test coverage.

Weeks 4–6

AI assistant and approved knowledge base

RAG implementation, content indexing, citations, escalation, feedback, and AI governance controls.

Weeks 5–6

Analytics and reporting

Dashboards, exports, indicator definitions, and reporting validation.

Weeks 6–7

System integration and end-to-end testing

Integration verification, end-to-end tests, defect tracking, and resolution.

Weeks 6–7

Security, privacy, performance and recovery testing

Security/privacy testing, load/performance testing, backup, and restoration verification.

Weeks 7–8

User acceptance testing and remediation

UAT, issue resolution, retesting and documented sign-off.

Week 9

Production deployment and training

Production release, operational readiness checks, administrator/end-user training and knowledge transfer.

Week 9

Final handover and acceptance

Source code and technical handover, final report, warranty/support plan and formal acceptance.

Acceptance Criteria:

• Offline learning is operational.
• All functional requirements are implemented.
• Android and iOS applications are operational and running on the Google Play Store and the Apple App Store.
• Knowledge transfer is completed.
• Documentation is submitted.
• UAT sign-off is achieved.
• Security testing is passed.
• AI assistant functions as specified.
• Reporting and dashboards are operational.
• Multilingual support is functional.

Proposal Submission Requirements

• Selected candidates will be required to work hybrid and travel to implementing states where required.
• Experience with cloud-hosted systems, APIs, data security, analytics and operational support.
• Demonstrated experience integrating AI/LLM functionality; practical RAG implementation experience is required for the AI scope.
• Demonstrated experience with offline-first mobile applications and data synchronisation.
• Experience with multilingual systems and, preferably, Hausa and Fulfulde language technology or validation.
• Experience in health or public sector digital systems is an advantage.
• At least five years of relevant mobile or enterprise application development experience.
• Demonstrated delivery of production learning, training, assessment, or workforce support platforms.

Proposed Consultant:

• The proposed consultant would identify named personnel, roles, availability and CVs for the project manager, mobile application lead, backend/API developer, AI/RAG specialist, UI/UX designer, QA/test lead and security/data protection expertise. One person may cover multiple roles where the provider demonstrates sufficient capacity and appropriate separation of duties.

Technical proposal requirements:

• Examples/references for comparable solutions and a transparent financial proposal.
• Technical architecture and proposed technology stack, including rationale and dependencies.
• Security, privacy, data management, and disaster recovery approach.
• Offline strategy, synchronization design, and testing approach.
• Understanding the assignment and proposed MVP/phased delivery approach.
• Work plan, milestones, team composition, risk register and support model.
• AI/RAG architecture, source governance, evaluation plan and cost controls.

Intellectual Property, Data Ownership and Handover:

• The provider must hand over complete, current source code for all custom-developed components, including mobile applications, backend, portal, integration services and AI/RAG orchestration/configuration.
• The provider must disclose open-source and commercial dependencies, licence conditions, model/provider dependencies and any restrictions on transfer or continued use.
• All code must be maintained in a repository accessible to the designated programme owner throughout development, not provided only at the end.
• The provider must provide reasonable transition support to a successor team under the agreed contract terms.
• Programme data must be returned or transferred in an agreed usable format at contract end; any copies held by the provider must be handled according to the agreed retention and deletion requirements.
• The provider must hand over deployment scripts, infrastructure configuration, data schema, migration/backup procedures, API documentation and environment configuration, with secrets transferred through a secure process.
• The provider would have completed knowledge transfer of the entire system architecture to a representative(s) of the programme.

How to Apply
Interested and qualified candidates should:
Click here to apply online

Note

• Our Safeguarding Policy outlines our responsibility to prevent abuse, harassment, and exploitation in all areas of our work. We expect everyone working with us staff, consultants, volunteers, and partners to adhere to this policy and our Code of Conduct.
• Interested and qualified candidates who are passionate and willing to contribute towards the achievement of our goals should kindly fill in the application form below and submit their resume in PDF Format 
• Safeguarding: Malaria Consortium is committed to protecting children and vulnerable adults and ensuring that all staff, partners, and representatives uphold the highest standards of ethical conduct.
• NB: Malaria Consortium does not accept or ask for payment during recruitment. We also would not accept hardcopy CVs; all applications should be sent through the above link.
• Kindly note that applications will be reviewed on a rolling basis, and as a result, the process may conclude before the advertised deadline. Therefore, early applications are highly encouraged.
• Safeguarding Requirement: Candidates must complete the Malaria Consortium Safeguarding Course on Kaya using this link Log in to the site |Kayaas you will be mandated to submit the certificate at the point engagement. Only candidates who provide a valid certificate will proceed with the engagement process.
• By following these standards, we help create safe environments and reduce any risk of harm in the communities we serve.
• Kindly note that applicants who do not follow this specification will be disqualified and only shortlisted candidates will be contacted.

Application Deadline: 11th November, 2026; 5:00PM.