Senior AI Engineer, Ethiopia

Responsibilities

Design & Develop

• Engage in the  development and enhancement of the HEP Assist AI platform for frontline Health Extension Workers (HEWs)
• Design and implement multilingual AI systems supporting Amharic and other Ethiopian local languages
• Develop and optimize prompt engineering workflows to improve AI response quality and user experience
• Fine-tune and evaluate Models for healthcare and community health use cases
• Build multimodal AI capabilities including voice-to-voice chat, speech recognition,audio and video processing
• Design and implement offline-first AI functionality for low-bandwidth and disconnected environments
• Develop and maintain Retrieval-Augmented Generation (RAG) and Graph RAG pipelines
• Build diagnostic AI agents and agentic AI workflows to support healthcare decision-making
• Develop secure backend APIs and services for data ingestion, processing, and exchange to support AI-powered healthcare applications

• Conduct model benchmarking, evaluation, hallucination testing, and LLM Judge assessments
• Improve AI chat interfaces and user experiences based on user research and field feedback
• Collaborate with cross-functional teams to prioritize AI product roadmap and deliver high-quality releases
• Integrate AI systems with telephony, messaging, mobile, and web platforms including IVR and voice-based services
• Design scalable infrastructure for model serving, vector databases, document pipelines, and realtime AI interactions

Deploy & Manage

• Configure, deploy, and maintain LLMs and AI services in cloud and on-premise environments
• Design and manage CI/CD pipelines for AI applications and model deployment workflows
• Implement monitoring, logging, observability, and performance optimization for AI systems
• Manage vector databases, embeddings infrastructure, GPU resources, and AI serving environments
• Ensure system scalability, reliability, security, and compliance with organizational standards
• Support deployment automation and infrastructure-as-code practices

Train & Support

• Provide technical mentorship and AI knowledge sharing across engineering and product teams
• Provide capacity-building activities for internal stakeholders and Ministry of Health
• Document AI architectures, deployment procedures, and engineering best practices
• Collaborate with global and local teams on innovation initiatives and digital health strategies

Skillset

• Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, Machine Learning, Information Technology, or related technical fields.
• Strong experience in AI/ML engineering, LLM application development, and production AI systems
• Demonstrable experience with model fine-tuning, prompt engineering, and model evaluation methodologies
• Strong understanding of Retrieval-Augmented Generation (RAG), Graph RAG, vector databases, and embeddings
• Experience building multilingual AI systems and improving local language model performance
• Experience developing multimodal AI systems including speech-to-text, text-to-speech, and voice interfaces
• Strong programming skills in Python and modern AI frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face, or equivalent
• Experience deploying and optimizing open-source and commercial LLMs in cloud and on-premise environments
• Strong understanding of agentic AI systems, orchestration frameworks, and AI workflow automation
• Experience with DevOps, CI/CD pipelines, Docker, Kubernetes, GitHub Actions, and infrastructure automation
• Experience with API development, backend systems, and scalable software architecture
• Experience with cloud platforms such as AWS, Azure, or GCP and GPU-enabled infrastructure
• Familiarity with data engineering, data pipelines, monitoring, and observability tools
• Strong problem-solving, collaboration, communication, and project management skills
• Experience working in healthcare, digital health, or low-resource settings is an advantage