Recruitment of a Senior AI/ML Engineer — Ministry of Finance and Economic Planning, Republic of Rwanda

Republic of Rwanda

Ministry of Finance and Economic Planning

P.O Box 158 Kigali, Rwanda

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REQUEST FOR EXPRESSIONS OF INTEREST

Recruitment for Individual Consultant Services (2nd Senior AI/ML Engineer) for the Integrated Financial Management Information System (IFMIS)

Background

The Government of Rwanda (GoR) is implementing the Revenue Improvement and Spending Efficiency (RISE) Program-for-Results (PforR) Operation with support from the World Bank. The Program aims to strengthen domestic revenue mobilization, improve efficiency in public spending, and enhance transparency and accountability in public financial management systems.

The Integrated Financial Management Information System (IFMIS) supports end-to-end public financial management processes, to improve operational efficiency, data quality, risk management, and decision support, IFMIS intends to implement AI and Machine Learning (ML) solutions that enhance forecasting, anomaly detection, process optimization, and user support, while maintaining strict requirements for security, auditability, compliance, and system performance.

Objective

The Government of Rwanda seeks to engage two (2) Senior AI/ML Engineer Individual Consultants through a single competitive selection process, from which two separate contracts will be awarded to the first and second ranked candidates. Each consultant will be engaged under an independent contract and will be individually accountable for the full scope of duties described in this Terms of Reference.

The consultants will design, develop, deploy, and maintain AI/ML solutions that enhance IFMIS business processes and analytics. Their work will focus on building production-ready, explainable, secure, and maintainable AI capabilities that seamlessly integrate with the IFMIS architecture and data environment. Although each consultant will operate under a separate contract, they are expected to collaborate within the same technical ecosystem to ensure timely delivery, coherence, and continuity of AI/ML operations across the IFMIS platform.

Scope of the Services

Under the supervision of the Financial Systems Development Programme Manager the two senior AI/ML Engineer Individual Consultants will work closely with IFMIS business teams, data engineers, software engineers, security teams, and stakeholders in the delivery of the assignment. The two consultants will operate within the same technical environment and are expected to coordinate their efforts to maximize efficiency, ensure continuity of AI/ML operations, and meet agreed delivery timelines.

The Individual Consultants will:

• Implement the already identified and approved AI/ML use cases for IFMIS by working with IFMIS business team and technical stakeholders to confirm objectives, clarify business rules, validate data readiness, define measurable success criteria, and translate each use case into a practical delivery plan. This includes confirming expected outputs, usage in IFMIS workflows, integration touchpoints, and operational constraints such as auditability, performance, security, and compliance.
• Assess and prepare the required IFMIS datasets needed to deliver the approved AI/ML use cases, including profiling data quality, defining cleaning and validation rules, and implementing feature engineering logic that is traceable and reproducible.
• Work closely with data engineering and database teams to ensure data pipelines support reliable training and inference, with proper documentation of data lineage, feature definitions, and consistent alignment to IFMIS master data structures.
• Design, develop, train, and evaluate machine learning and/or NLP models aligned to the approved IFMIS use cases, selecting appropriate approaches and baselines and improving them iteratively based on agreed metrics.
• Define evaluation methodologies, performance thresholds, and validation processes that fit the operational and governance needs of IFMIS, including explainability requirements where decisions must be justified to auditors and business owners, and ensuring that model outputs are stable and reliable under real-world transactional behaviors.
• Package and deploy models into production-ready services for integration with IFMIS modules through agreed integration patterns, such as REST APIs, scheduled batch inference, or event-driven processing where applicable.
• Implement MLOps practices to ensure repeatable training, version control for models and features, automated deployment pipelines, and operational monitoring for reliability, latency, errors, and performance trends, including clear rollback mechanisms and controlled release approaches to reduce risk in production environments.
• Ensure that all AI/ML implementations comply with IFMIS security and governance requirements by applying secure-by-design practices, enforcing appropriate access controls, protecting sensitive data, and ensuring encryption and secure logging practices are applied as required.
• Produce governance documentation that supports traceability and audit readiness, including model documentation, training data provenance, feature references, assumptions, limitations, and risk considerations, ensuring that AI/ML outputs remain defensible and aligned with institutional compliance expectations.
• Produce comprehensive technical documentation supporting the full lifecycle of the delivered AI/ML solutions, including architecture descriptions, data flows, API specifications, deployment guides, and operational run-books. The Engineer will also conduct structured knowledge transfer to IFMIS technical teams through walk-throughs, training sessions, and handover support to ensure internal capacity to operate, monitor, maintain, and enhance the AI/ML solutions beyond the assignment period.
• Provide in-depth technical support to the IFMIS Administration team to investigate, troubleshoot, resolve, and escalate complex user-reported and system-generated incidents, collaborating with relevant technical teams to ensure timely resolution.
• Requirements for the Consultant The individual consultant should have the following demonstrable profile:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, Software Engineering, or a related field; a Master’s degree is an added advantage.
• Minimum of five (5) years of relevant experience in AI/ML engineering, including delivery of production-grade ML solutions beyond experimentation, with demonstrated ownership from model development through deployment and operational support.
• Strong proficiency in Python for ML development and data analysis, including core libraries such as NumPy, pandas, and scikit-learn; experience with at least one deep learning framework (e.g., TensorFlow or PyTorch); knowledge of Java/Spring) is an added advantage.
• Familiarity with Large Language Models (LLMs) and applied NLP, including prompt design, retrieval-augmented generation (RAG), embeddings, and evaluation of LLM outputs; ability to integrate LLM-based capabilities into enterprise applications with appropriate safeguards (privacy, access control, auditability, and hallucination mitigation)
• Proven ability to design, train, evaluate, and optimize ML models (e.g., classification, regression/forecasting, anomaly detection, clustering and/or NLP), including clear definition of metrics, validation strategy, and model selection aligned to business requirements.
• Experience applying responsible and explainable AI practices suitable for audit and governance needs, including model interpretability approaches (e.g., SHAP/LIME or interpretable baselines), documentation of assumptions/limitations, and reproducibility of experiments.
• Demonstrated capability to integrate and deploy ML models within enterprise systems using modern deployment practices, including API-based inference (e.g., FastAPI/Flask) and/or batch scoring pipelines, containerization (Docker), and CI/CD pipelines (e.g., GitLab CI).
• Working knowledge of data pipelines required for ML solutions, including data preparation, feature engineering, validation, and orchestration using tools such as Airflow (or equivalent), as well as an understanding of streaming/event-driven patterns where applicable.
• Strong SQL skills and experience working with relational databases (PostgreSQL and/or Oracle), including ability to analyze high-volume transactional data and apply performance-aware querying and data extraction approaches.
• Familiarity with MLOps practices and tools for experiment tracking, model versioning, and lifecycle management (e.g., MLflow or equivalent), including basic monitoring concepts such as data drift, model performance tracking, and operational alerting.
• Strong understanding of SDLC and proven involvement in key phases including requirements analysis, solution design, development, testing, deployment, and production support, with practical experience working in Agile environments (Scrum/Kanban).
• Strong analytical, interpersonal, and communication skills, with ability to collaborate effectively with both technical and non-technical stakeholders and to translate business needs into implementable technical solutions.
• Ability to work independently and as part of a wider team, conduct code reviews, ensure quality standards, and maintain well-documented, secure, and maintainable deliverables.
• Excellent fluency in English or French; working knowledge of the other language is an added advantage. The Ministry of Finance and Economic Planning now invites eligible consultants to indicate their interest in providing the services. Interested consultants must provide information indicating that they are qualified to perform the services through E-Procurement (www.umucyo.gov.rw )