• Develop and optimize prompts for generative AI models, with a particular focus on Voice AI • Conduct tests to improve model performance, accuracy, and relevance of outputs • Fine-tune and automate input commands (prompts) to increase efficiency and consistency • Analyze usage data and model outputs to enable continuous improvements and data-driven decisions • Integrate and calibrate Voice AI systems based on platforms such as fonio, vapi ai, retell ai, ElevenLabs, or Deepgram • Develop, train, and maintain internal Voice AI prototypes and workflows • Monitor current trends and technical developments in generative AI, prompt engineering, and speech models to advance internal strategies

• Research and implement state-of-the-art techniques to accelerate AI inference • Partner closely with hardware, compiler, and quantization teams • Build profiling tools and comprehensive benchmarking frameworks • Build robust fine-tuning workflows for modern AI models

• Design and develop software applications that incorporate AI and Machine Learning models • Integrate AI models with existing systems, APIs, data pipelines, and distributed architectures • Collaborate with Data Scientists and Data Engineers on building, training, versioning, and deploying models • Implement MLOps practices to ensure automation, monitoring, traceability, and scalability of models in production • Develop solutions based on LLMs (Large Language Models), such as chatbots, recommendation systems, classification, semantic search, and intelligent automation • Ensure code quality, security, performance, and software engineering best practices • Participate in architectural decisions, technical reviews, and the definition of standards • Drive continuous improvement of solutions by evaluating model and software performance metrics • Document technical solutions and share knowledge with the team

• Lead and facilitate weekly live online sessions using structured course materials. • Supervise Assistant Facilitators, ensuring consistent learner engagement and marking quality. • Provide 1-to-1 guidance and academic feedback to learners in line with defined rubrics. • Monitor and maintain high standards of delivery, assessment, and learner satisfaction. • Collaborate with internal academic and delivery teams to manage content updates and resolve challenges. • Participate in programme review discussions, sharing insights for continuous improvement. • Represent the programme in internal panels or forums as required. • Ensure all academic activity aligns with established frameworks and standards.