AI Developer

Athena Institute of Business and Technology (AIBT) is building Africa’s next generation of business, policy, and tech leaders, through flexible, practical, and impact-driven learning.

We are recruiting to fill the position below:

Job Title: AI Developer

Location: Remote

Employment Type: Full-time

Job Description

• We are seeking a skilled and innovative AI Developer to design, develop, implement, and maintain artificial intelligence solutions that improve business processes, automate tasks, and support data-driven decision-making.
• The successful candidate will be responsible for building AI-powered applications, integrating machine learning models and large language models (LLMs) into existing systems, and developing intelligent solutions that address real-world business challenges. The ideal candidate should have strong programming skills, a solid understanding of artificial intelligence and machine learning concepts, and practical experience developing, testing, deploying, and maintaining AI applications.

Key Responsibilities

• Design, develop, test, and deploy AI-powered applications and intelligent software solutions based on business requirements.
• Develop and integrate machine learning models for prediction, classification, recommendation, automation, and other business use cases.
• Build applications that leverage large language models (LLMs), generative AI, natural language processing (NLP), and other AI technologies.
• Integrate AI capabilities into existing enterprise applications, websites, APIs, databases, and business workflows.
• Develop and maintain AI-driven chatbots, virtual assistants, document processing tools, and automated customer support solutions.
• Prepare, clean, transform, and analyze datasets for model training, evaluation, and deployment.
• Design and implement Retrieval-Augmented Generation (RAG) solutions that enable AI applications to retrieve and use relevant information from organizational data sources.
• Work with AI frameworks, libraries, and APIs to develop reliable and scalable intelligent applications.
• Evaluate model performance, accuracy, reliability, latency, and cost, implementing improvements where necessary.
• Implement appropriate testing, monitoring, logging, and error-handling mechanisms for AI applications.
• Apply responsible AI principles, including data privacy, security, fairness, explainability, and mitigation of harmful or inaccurate outputs.
• Collaborate with software developers, data engineers, business analysts, and other stakeholders to identify opportunities for AI adoption.
• Document AI application architecture, development processes, model performance, and technical specifications.
• Research emerging AI technologies and recommend practical solutions that align with organizational objectives.
• Maintain and improve deployed AI solutions through regular updates, performance monitoring, and continuous optimization.

Requirements

Education

• Bachelor's Degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, Computer Engineering, Mathematics, Statistics, or a related discipline.
• Relevant professional training in machine learning, generative AI, deep learning, or AI application development will be an added advantage.
• Industry-recognized certifications in AI, machine learning, or cloud-based AI technologies are desirable.
• Equivalent practical experience, demonstrable technical expertise, and a strong portfolio of AI projects may be considered.

Experience

• 3–5 years of relevant experience in software development, AI engineering, machine learning, or a related technical role.
• Demonstrable experience developing, testing, and deploying AI-powered applications or machine learning solutions.
• Practical experience using Python and relevant AI or machine learning frameworks.
• Experience integrating AI models or LLM services into applications using APIs and SDKs.
• Familiarity with data preparation, model evaluation, application testing, and deployment processes.
• Experience building AI chatbots, intelligent assistants, RAG applications, recommendation systems, or comparable solutions will be an advantage.
• Demonstrated ability to translate business problems into scalable, maintainable, and measurable AI solutions.
• Experience collaborating with multidisciplinary teams and communicating technical concepts to non-technical stakeholders.

Required Skills

• Strong programming skills in Python and familiarity with software development best practices.
• Good understanding of artificial intelligence, machine learning, deep learning, and relevant statistical concepts.
• Experience working with AI and machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Knowledge of generative AI, large language models (LLMs), prompt engineering, and AI application development.
• Experience integrating AI models through APIs and software development kits (SDKs).
• Understanding of natural language processing (NLP), text processing, and information retrieval.
• Familiarity with Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
• Experience developing REST APIs and integrating AI solutions with existing software applications.
• Knowledge of SQL, database management, data preprocessing, and data validation.
• Understanding of model evaluation, performance optimization, testing, and deployment.
• Familiarity with Git, version control, debugging, and collaborative software development.
• Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Understanding of AI security, data privacy, access controls, and responsible AI practices.
• Strong analytical, critical-thinking, and problem-solving skills.
• Excellent communication skills and the ability to translate business requirements into practical AI solutions.

Additional Advantage:

• Experience with AI agent development, tool calling, and workflow orchestration.
• Familiarity with frameworks such as LangChain, LlamaIndex, or comparable AI development tools.
• Experience with Docker, Kubernetes, CI/CD pipelines, and cloud-based deployment.
• Knowledge of MLOps, model monitoring, model versioning, and automated deployment pipelines.
• Experience with fine-tuning or adapting pretrained models for specific business applications.
• Familiarity with multimodal AI involving text, images, audio, or video.
• Experience implementing AI solutions in enterprise environments.
• Relevant certifications in artificial intelligence, machine learning, cloud computing, or data science.

Application Closing Date

27th October, 2026.