{"id":3563281,"url":"https://alion.io/job/malaria-consortium-cross-platform-mobile-application-developer-consultant-2","title":"Cross-Platform Mobile Application Developer (Consultant)","company":{"id":1772449,"name":"Malaria Consortium","domain":"malariaconsortium.org","url":"https://alion.io/company/malariaconsortium","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Abuja, Nigeria"],"countries":["NG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Flutter","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"MVP","optional":false},{"name":"Node JS","optional":false},{"name":"Offline-First","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React Native","optional":false},{"name":"Rest API","optional":false},{"name":"C#","optional":true},{"name":"Dart","optional":true},{"name":"JavaScript","optional":true},{"name":"React.js","optional":true}],"status":"live","first_seen_at":"2026-10-30T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-30T00:00:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"The overall objective is to engage a highly experienced cross-platform mobile application consultant with demonstrated expertise in Artificial Intelligence integration to:\n\nDesign and develop a secure mobile learning platform for Android and iOS.\n\nBuild multilingual training and assessment capabilities.\n\nDevelop an AI-powered assistant based on approved SARMAAN II knowledge sources.\n\nEnable offline learning and synchronization.\n\nProvide comprehensive management and administrative portals.\n\nDeliver scalable analytics and reporting capabilities.\n\nEnsure compliance with data privacy and security standards.\n\nDeploy, train administrators, and provide post-implementation support.\n\nScope of Work\nThe 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.\n\nThe application must support Android and iOS devices, low-bandwidth environments, offline-first architecture, and synchronization services to ensure seamless access and data synchronization.\n\nThe platform architecture should incorporate services and functionalities for user administration, content management, assessment configuration, AI governance, reporting, and monitoring.\n\nThese 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.\n\nQualifications and Requirements\nThe consultant must demonstrate:\n\nMinimum of 5 years’ experience in mobile application development.\n\nMinimum of 3 years’ experience deploying AI-enabled solutions and similar applications to be built.\n\nProven experience delivering learning management platforms.\n\nExperience implementing multilingual solutions.\n\nExperience supporting offline-first applications.\n\nExperience deploying cloud-based enterprise systems.\n\nStrong experience in:\n\nFlutter or React Native\n\nAndroid and iOS development\n\nPython, .NET, Node.js, Java or equivalent backend technologies\n\nAI/LLM integration\n\nRetrieval Augmented Generation (RAG)\n\nVector databases\n\nKnowledge management systems\n\nRESTful APIs\n\nCloud platforms (Azure, AWS or GCP)\n\nData security and privacy compliance\n\nAnalytics and dashboard development\n\nHealth sector digital platforms\n\nTraining and capacity building systems\n\nAI governance frameworks\n\nMultilingual African language solutions.\n\nFunctional Requirements\nThe system should support user registration and authentication through role-based access control, allowing access to features and functionalities based on assigned user roles.\n\nUsers should be able to log in using their phone number or unique ID and authenticate using a password or PIN.\n\nThe system may also optionally support OTP authentication and configurable security policies to enhance security and access management.\n\nPrivacy and Consent Management\nThe 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.\n\nThe 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.\n\nWhere a user declines to provide consent, the system must prevent further access and redirect the user to the welcome page.\n\nMultilingual Capability\nThe platform should provide:\n\nThe 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.\n\nLearning Management Features\nThe dashboard should display:\n\nAssigned learning path\n\nLearning progress\n\nAssessments\n\nCertificates\n\nOutstanding learning requirements\n\nThe system should support role-based learning pathways for: CDD, OIC, HFW, Supervisors and additional cadres as may be configured.\n\nLearning paths should include: Mandatory modules, Optional modules, Assessments and Certification requirements.\n\nEach 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.\n\nLearning Content Delivery:\n\nFeatures: Scroll, Read, Bookmark, Play, Pause and Replay. Requirements: Low-bandwidth optimization.\n\nFeatures: Play, Pause and Replay. Requirements: Optimized streaming, Download capability and Low-bandwidth versions.\n\nLearning Integrity Controls\n\nThe 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.\n\nThe 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.\n\nThe platform should measure baseline knowledge and automatically score responses.\n\nWhere learners fail:\n\nRelevant content must be revisited\n\nReattempt policies must be enforced\n\nGuessing behavior should be minimized.\n\nModule completion should require:\n\nMinimum learning time met\n\nContent consumption completed\n\nKnowledge checks completed\n\nAssessment criteria achieved.\n\nCertificate Management\n\nAutomatically generate certificates\n\nAllow certificate download\n\nStore certificate records.\n\nRecommended features:\n\nQR Code verification\n\nCertificate validation service.\n\nOffline Learning Capability\nBecause deployment targets field personnel working in low-connectivity environments, offline capability is mandatory.\n\nThe 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.\n\nOffline 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.\n\nThe system should:\n\nSync automatically\n\nAllow manual sync\n\nResolve conflicts\n\nDisplay last synchronization date/time.\n\nAI Requirements\nThe proposed solution must include advanced AI functionality powered by secure Retrieval-Augmented Generation (RAG).\n\nThe mobile application should provide: Conversational question-and-answer functionality, Learning support and Procedure guidance.\n\nRequirements:\n\nMaximum question size configurable\n\nGrounded responses only\n\nNo hallucinated content.\n\nThe 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.\n\nThis 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.\n\nThe 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.\n\nRAG Knowledge Base\nThe AI architecture should include only approved content, which should be indexed, including:\n\nePlaybooks\n\nSOPs\n\nTraining manuals\n\nFAQs\n\nApproved programme documentation\n\nThe AI should never use unrestricted internet content when answering learner questions.\n\nThe 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.\n\nThe 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.\n\nFurthermore, 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.\n\nWhere confidence levels are low, the system should:\n\nEscalate to Trainer\n\nEscalate to Supervisor\n\nFlag unresolved questions\n\nThe AI should not fabricate information.\n\nAI Feedback System\nLearners should be able to rate AI responses. Ratings should support:\n\nAnalytics\n\nContinuous improvement\n\nKnowledge gap analysis\n\nAdministrators should be able to:\n\nManage source documents\n\nConfigure AI behavior\n\nDefine restricted topics\n\nConfigure escalation rules.\n\nThe platform should record:\n\nQuestions submitted\n\nResponses generated\n\nFeedback received\n\nEscalations raised\n\nUnanswered questions while enforcing privacy controls and retention rules.\n\nAdministrators should be able to:\n\nUpload new content\n\nApprove content\n\nPublish content\n\nArchive content\n\nThe AI must index only approved content. Version control is mandatory.\n\nManagement Portal Requirements\nThe system should include a web-based management portal. Provide visibility into:\n\nProgramme performance\n\nCompletion rates\n\nPass rates\n\nRetention rates\n\nLearning progress.\n\nCapabilities should include:\n\nCreate users\n\nUpdate users\n\nDeactivate users\n\nAssign roles.\n\nRoles include:\n\nLearner\n\nTrainer\n\nSupervisor\n\nAdministrator\n\nManagement\n\nThe system should implement least-privilege access principles.\n\nThe management portal should provide:\n\nCDD performance analytics\n\nOIC performance analytics\n\nHFW performance analytics\n\nSupervisor performance analytics\n\nFilters should include State, LGA, Facility and Role.\n\nTrack: Completed training, Pending training and Overdue training.\n\nMonitor:\n\nTime spent\n\nModule progress\n\nCompletion rates\n\nLearning trends\n\nThe solution should identify:\n\nUnusually fast completion\n\nRepeated suspicious behavior\n\nand generate alerts.\n\nProvide:\n\nState-level performance reporting\n\nLGA-level reporting\n\nFacility-level reporting\n\nusing map and chart visualizations.\n\nMonitor:\n\nScores\n\nCompletion rates\n\nFailure rates\n\nto identify weak content areas.\n\nContent Management System (CMS)\nManage the following content types:\n\nLearning content\n\nModules\n\nFAQs\n\nSOPs\n\nDocuments\n\nAI knowledge sources\n\nCapabilities should include:\n\nCreate\n\nEdit\n\nReview\n\nApprove\n\nPublish\n\nArchive\n\nVersion control is mandatory.\n\nAssessment Management\n\nQuestion creation\n\nQuestion editing\n\nTest configuration\n\nApproval workflows.\n\nQuestion types may include:\n\nMultiple choice\n\nTrue/false\n\nMatching\n\nScenario-based questions\n\nDifficulty levels should be confi...","description_format":"text","description_chars":17332,"description_truncated":true,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Mobile Games"],"lifecycle":[{"event":"open","at":"2026-10-31T06:47:35Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":1,"expected_fill_days":24,"reasons":["seen:1","win:early"],"computed_at":"2026-10-31T17:37:36Z"},"pay":null,"html_url":"https://alion.io/job/malaria-consortium-cross-platform-mobile-application-developer-consultant-2","json_url":"https://alion.io/job/malaria-consortium-cross-platform-mobile-application-developer-consultant-2.json","meta":{"generated_at":"2026-10-31T17:37:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":27584,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1772449},"rest":"https://alion.io/mcp/rest/get_company?id=1772449"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmalaria-consortium-cross-platform-mobile-application-developer-consultant-2"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fmalaria-consortium-cross-platform-mobile-application-developer-consultant-2"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fmalaria-consortium-cross-platform-mobile-application-developer-consultant-2"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/malaria-consortium-cross-platform-mobile-application-developer-consultant-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmalaria-consortium-cross-platform-mobile-application-developer-consultant-2"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3563281}},{"tool":"search_jobs","arguments":{"company":"malariaconsortium.org","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3563281},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. Docs: https://alion.io/developers"}}