Lead AI Engineer

We are looking for a highly experienced Lead AI Engineer who is a core AI/ML professional with strong hands-on expertise in designing, developing, and deploying AI/ML systems at scale. The ideal candidate should have a deep understanding of Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, NLP and LLM technologies, along with strong Python programming and production engineering capabilities. This is a hands-on technical leadership role. We are looking for someone who can work beyond simply integrating third-party AI APIs and can contribute to AI model development, experimentation, optimisation, evaluation and productionization.

We are specifically looking for a Core AI Engineer, not someone whose experience is limited to calling OpenAI/LLM APIs or building basic chatbot applications. The ideal candidate should have a strong foundation in AI/ML algorithms, deep learning, model development, experimentation and production AI systems, combined with modern GenAI/LLM expertise.

Responsibilities:

• Lead the design and development of scalable AI/ML solutions for complex business problems.
• Develop, train, fine-tune, evaluate and optimise machine learning and deep learning models.
• Work extensively with Generative AI, LLMs, NLP and advanced AI architectures.
• Design AI pipelines covering data preparation, model training, evaluation, deployment and monitoring.
• Build and productionize AI models using Python and modern AI/ML frameworks.
• Work on LLM fine-tuning, prompt engineering, RAG, embeddings and vector databases where applicable.
• Evaluate AI models using appropriate accuracy, performance and business metrics.
• Research and implement state-of-the-art AI/ML techniques.
• Collaborate with Data Engineering, Backend Engineering, Product and Business teams.
• Establish best practices around model versioning, experimentation, reproducibility and AI governance.
• Mentor senior engineers and guide the technical direction of AI initiatives.
• Drive AI solutions from POC to production to continuous optimisation.

The core requirements for the job include the following:

Core AI / Machine Learning:

• Strong hands-on experience in Machine Learning and Deep Learning.
• Strong understanding of Supervised and Unsupervised Learning.
• Experience with model development, training, validation and optimisation.
• Strong knowledge of NLP and/or Computer Vision.
• Experience with neural network architectures and modern deep learning techniques.

Generative AI / LLM:

• Strong practical experience with Generative AI and Large Language Models.
• Experience with LLM fine-tuning/customisation.
• RAG (Retrieval-Augmented Generation).
• Prompt Engineering.
• Embeddings and Vector Search.
• AI/LLM evaluation.
• Experience with frameworks such as LangChain, LlamaIndex or equivalent.

Programming and Frameworks:

• Strong proficiency in Python.
• Experience with PyTorch and/or TensorFlow.
• Strong understanding of NumPy, Pandas and the ML ecosystem.
• Experience developing production-grade AI applications and services.

AI Infrastructure / Deployment:

• Experience deploying AI/ML models into production.
• Knowledge of MLOps / ML lifecycle management.
• Experience with Docker and containerised deployments.
• Knowledge of cloud platforms such as AWS, GCP or Azure.
• Understanding of model monitoring, performance optimisation, and scalability.

Good to Have:

• Experience with Generative AI Agents / Agentic AI.
• Experience with multimodal AI.
• Knowledge of Transformer architectures.
• Experience with open-source LLMs such as Llama, Mistral or similar.
• Experience with distributed model training/inference.
• Knowledge of Kubernetes.
• Experience with MLflow, Kubeflow or similar MLOps platforms.
• Strong understanding of AI system architecture and scalability.

Leadership Expectations:

• Proven ability to technically lead AI engineering teams/projects.
• Strong problem-solving and architectural thinking.
• Ability to independently drive AI initiatives from concept to production.
• Ability to mentor and review the work of AI/ML engineers.
• Strong communication and stakeholder-management skills.
• Comfortable working in a fast-paced, product-focused environment.

Education:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering or a related field.
• An advanced degree in AI/ML or related specialisation will be an advantage.

Key Skills:

• Core AI | Machine Learning, Deep Learning, Generative AI, LLM, NLP, Python, PyTorch, TensorFlow, RAG, LLM Fine-Tuning, Transformers, LangChain, Vector Databases, MLOps, AI Model Deployment, Cloud, AI Architecture.