6 Jobs At ALX
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Nairobi, Kenya
Job summary
Remote Roles at ALX
About this role
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Contents
Open Jobs
Financial Controller
AI Engineer
Learning Scientist
LLMOps Engineer
Senior AI/ML Engineer
Technical Product Manager
FINANCIAL CONTROLLER
About the Role
The Financial Controller will play an important role in strengthening and managing the financial operations of ALX. The position will be responsible for maintaining the accuracy, integrity, and effectiveness of the organisation’s financial activities across its different operations.
The role will oversee key areas including accounting, financial controls, financial reporting, treasury, taxation, and compliance. In addition to managing these core functions, the Financial Controller will provide financial information and insights that support sustainable organisational growth, sound decision-making, and operational effectiveness.
Working closely with the VP of Finance, executive leadership, and external stakeholders, the Financial Controller will support strong financial governance across multiple jurisdictions. The position will also contribute to strengthening internal controls and ensuring that applicable financial and regulatory requirements are consistently met.
A major part of the role will involve developing scalable financial processes, systems, and reporting structures that can support a growing organisation. The successful candidate will therefore need to combine strong technical accounting knowledge with commercial understanding, leadership ability, and a commitment to continuous improvement.
Key Responsibilities
Financial Management and Control
The Financial Controller will oversee the organisation’s accounting and financial control activities, ensuring that financial information is accurate, reliable, and produced within appropriate reporting requirements.
The role will involve maintaining effective financial controls, strengthening governance processes, and ensuring that financial operations remain effective as the organisation expands across different jurisdictions.
Financial Reporting
The position will oversee financial reporting activities and ensure that management receives reliable information to support informed decision-making.
The Financial Controller will contribute to the development of effective reporting frameworks that provide visibility into financial performance and support operational planning.
Treasury and Tax
The role will provide oversight of treasury and tax functions while ensuring that financial activities comply with relevant requirements across the jurisdictions in which the organisation operates.
The successful candidate will be expected to maintain effective financial processes and support appropriate management of financial obligations.
Compliance and Internal Controls
The Financial Controller will drive financial governance and strengthen internal controls across the organisation.
Responsibilities will include ensuring that financial processes comply with applicable requirements, identifying opportunities to improve controls, and supporting consistent financial governance across multiple entities and jurisdictions.
Financial Systems and Infrastructure
The successful candidate will contribute to building financial operations, systems, and infrastructure that can support a high-growth organisation.
This will include establishing scalable processes and reporting frameworks that enable the finance function to operate effectively as the organisation continues to expand.
Essential Skills and Experience
Financial Control Experience
The candidate should have proven experience working as a Group Financial Controller or in an equivalent position within a complex multinational organisation.
Accounting and Tax Knowledge
Strong knowledge of international accounting standards, including IFRS and GAAP, is required. The candidate should also have a strong understanding of relevant tax regulations.
Finance Operations
Experience establishing finance operations and developing financial systems and infrastructure within a high-growth organisation is required.
Financial Analysis
The successful candidate should possess advanced knowledge of financial analysis, budgeting, and forecasting techniques.
Complex Business Structures
The candidate should understand large and complex business structures and groups and be capable of managing financial activities within such environments.
Leadership and People Management
Strong leadership and people management skills are essential. The candidate should be able to lead teams effectively and contribute to the development of a strong finance function.
Communication
Excellent communication and interpersonal skills are required to work effectively with executive leadership, internal teams, auditors, and other external stakeholders.
Financial Technology
The candidate should be proficient in financial software and systems, including enterprise resource planning systems and business intelligence tools.
Analytical and Problem-Solving Ability
A strong analytical mindset and high level of attention to detail are required. The candidate should take a proactive and practical approach to identifying financial issues and developing appropriate solutions.
Commercial Mindset
The ideal candidate should have a strong interest in financial excellence and be able to contribute to the organisation’s growth through effective financial management and continuous improvement.
Preferred Skills and Experience
Professional Accounting Qualification
A professional accounting qualification such as ACCA, ACA, CPA, or an equivalent qualification is preferred, particularly where combined with experience working in a complex, multi-entity finance environment.
Team and Stakeholder Management
Experience managing and developing finance teams is preferred. The candidate should also have experience working with external stakeholders, including auditors, business owners, or donors.
Additional Languages
Knowledge of additional languages, particularly French and/or Arabic, would be an advantage.
AI ENGINEER
Role Summary
The AI Engineer will support the development of Project A, ALX’s AI-enabled learning platform. The platform includes AI capabilities covering learner onboarding and profiling, project guidance, project deconstruction, and content mapping connected to a competency model.
The role will focus on transforming AI prototypes into dependable products that learners can use consistently. The engineer will take responsibility for the systems learners interact with, including context engineering, agent tooling, service interfaces, and the systems required to make long-running and multi-step AI agents dependable.
The successful candidate will work with Anthropic engineers, AI engineers, product managers, and data scientists to create effective learning experiences.
Essential Skills
Python and FastAPI
Strong production-level experience with Python and FastAPI, including experience working with systems used by real users.
LLM Applications
Experience shipping at least one AI or LLM application and being able to explain what failed, how those failures were identified, and what improvements were made.
Agent Frameworks
Practical experience with agent frameworks such as LangGraph or comparable technologies, together with a strong understanding of context engineering.
Testing
A disciplined approach to testing software and ensuring that systems are reliable.
AI-Native Development
Demonstrated experience with AI-native coding and harness engineering.
Desirable experience includes React and broader full-stack capabilities, Langfuse or comparable observability tools, and knowledge graphs. Experience in education technology is also useful.
LEARNING SCIENTIST
Role Summary
The Learning Scientist will guide pedagogical decision-making across the platform, contributing during product design and evaluating learning effectiveness after implementation.
The role will involve interpreting the ALX learning framework and ensuring that the platform is grounded in practical learning science rather than simply incorporating educational terminology.
The successful candidate will help design experiments around the platform’s key pedagogical assumptions and work with the experimentation function to assess whether specific product features genuinely support learning.
The role will also involve working with engineers to evaluate AI products and translate learning science principles into practical product decisions.
Essential Skills
Learning Science
Strong understanding of learning science and the ability to apply established modern frameworks rather than relying only on personal teaching experience or intuition.
AI Literacy
Understanding of the capabilities and limitations of LLM-based tools sufficient to collaborate effectively with engineers during product development.
Experiment Design
Ability to formulate hypotheses, establish appropriate measures, and apply sufficient methodological rigour to evaluate learning-related claims.
Desirable experience includes previous EdTech product work, familiarity with competency frameworks or knowledge tracing, and experience with African education contexts.
Essential Traits
The successful candidate should be comfortable challenging assumptions across the team, including technical decisions where appropriate.
The candidate should be able to work across disciplines and communicate effectively within an engineering-focused environment.
They should also be able to describe a pedagogical belief they changed and explain the evidence that influenced that change.
LLMOPS ENGINEER
Role Summary
The LLMOps Engineer will support ALX’s AI learning platform by analysing the data generated by its various LLM-based products and determining whether those products are performing as intended.
The role will involve breaking AI products into measurable components and identifying the different ways in which each component can succeed or fail. For example, a retrieval-augmented generation system may involve separate concerns around document storage, retrieval accuracy, and the quality of the retrieved information.
The position is designed as a junior-to-mid-level opportunity with a defined development path. The successful candidate will initially work closely with the technical lead and progressively develop toward full ownership of the function.
Essential Skills
Python and Data
Solid Python capability and an analytical approach to working with complex and unstructured LLM-generated data.
Product Decomposition
Ability to analyse an AI product and break it down into measurable success and failure indicators.
Evaluation Tools
Familiarity with tools such as Langfuse, RAGAS, DSPy, or comparable evaluation technologies. Depth in one tool is sufficient, provided the candidate understands the underlying principles.
Desirable experience includes keeping evaluation processes cost-effective at scale, dashboard creation, reporting, and classical statistics.
Essential Traits
The successful candidate should want to take ownership of a function rather than simply completing assigned tickets.
Strong communication and collaboration skills are important because the role will support builders across the team.
The candidate should also be able to demonstrate an example of measuring an AI system objectively, even if the project was relatively small.
SENIOR AI/ML ENGINEER
Role Summary
The Senior AI/ML Engineer will work on the core competency model within Project A and address the central algorithmic challenge of determining what a learner should do next based on available information about their knowledge and progress.
The role involves developing a probabilistic path-recommendation system related to approaches such as Bayesian Knowledge Tracing and Knowledge Space Theory. The system must operate effectively from a cold start, meaning that there will initially be limited behavioural data available.
The engineer will therefore need to incorporate the prerequisite structure of the learning domain and progressively update the model as learner data becomes available.
Essential Skills
Probabilistic Modelling
Deep experience designing probabilistic or Bayesian models based on domain structures rather than simply fitting models to existing datasets.
Python and Production Delivery
Strong Python skills and the ability to turn models into production systems and pipelines rather than limiting work to notebooks.
Evaluation
Experience designing evaluations or the ability to establish effective evaluation processes quickly.
Desirable experience includes Bayesian Knowledge Tracing, Knowledge Space Theory, psychometrics, MLflow or similar experiment tracking tools, and knowledge graphs. Experience with structured-domain modelling such as recommenders, causal inference, or knowledge graphs is valuable.
Essential Traits
The candidate should carefully examine assumptions because incorrect priors can compound silently in a cold-start model.
They should be capable of learning unfamiliar domains quickly and be comfortable working through complex problems.
The candidate should also be able to explain an example of a model that produced incorrect results and how the problem was identified.
TECHNICAL PRODUCT MANAGER
Role Summary
The Technical Product Manager will support Project A, ALX’s AI learning platform, by determining which assumptions about learning and AI are supported by evidence and which require reconsideration.
The role will focus on reducing uncertainty through structured experimentation rather than concentrating primarily on product vision.
The successful candidate will own the experimentation function, ensuring that AI products are properly instrumented, sourcing learners for beta programmes, coordinating ongoing testing, reviewing results, and ensuring that findings lead to product improvements and subsequent prototypes.
The role will consider both learning effectiveness and user experience, ensuring that the organisation understands not only whether a product supports learning but also whether learners can use it effectively.
Essential Skills
Product Experimentation
Experience running product experiments from beginning to end, including establishing hypotheses, implementing instrumentation, analysing results, and making decisions. Experience with A/B testing or structured testing of live products is required.
Technical Understanding
The candidate should be technically fluent enough to discuss product instrumentation, interpret AI evaluation results, and collaborate effectively with engineers without necessarily being responsible for daily coding.
Operational Capability
Strong ability to recruit and coordinate real users, manage beta programmes, and coordinate different stakeholders.
Desirable experience includes hands-on evaluation or analytics skills and previous experience in EdTech.
Essential Traits
The successful candidate should have a scientific approach to experimentation and understand what different experiments can and cannot demonstrate.
They should be comfortable conducting experiments that challenge existing assumptions and potentially disprove ideas that initially appeared promising.
The candidate should also demonstrate strong practical problem-solving ability, including the ability to develop realistic approaches to recruiting beta learners within limited resources and timeframes.
Method of Application
Use the link(s) below to apply on company website.