AI Engineer

Duties

• Develop, optimise, deploy and maintain end-to-end AI/ML pipelines, from training and packaging through monitoring and lifecycle management.
• Develop, test, document, refactor and maintain AI/ML components, programs and scripts.
• Apply machine learning and data science to new datasets; evaluate model performance, data quality and outcomes.
• Troubleshoot and improve ML models, pipelines, datasets and AI development processes.
• Build and maintain data pipelines, including ETL/ELT.
• Develop AI modules and integrate them into builds, validating functionality, security, quality and performance.
• Support the full AI/software engineering lifecycle, including requirements, automation, testing, release, deployment and monitoring.
• Implement secure and maintainable engineering practices, including MLOps/AIOps, CI/CD and automation.
• Monitor AI technologies and contribute to technology assessments, roadmaps and knowledge sharing.
• Report progress, risks and blockers and collaborate with technical teams.

Key Requirements

• Strong hands-on experience in Python, machine learning, software engineering and applied AI.
• Strong understanding of ML concepts, model evaluation, performance measurement and model improvement.
• Practical experience with LLMs, foundation models, Generative AI and pre-trained models.
• Strong experience with RAG, embeddings, vector databases and AI application architectures.
• Experience building production-grade AI agent backends, using LangChain, LlamaIndex, Pydantic AI or similar.
• Strong MLOps/AIOps experience, including Git/version control, CI/CD, automation and model/experiment lifecycle management.
• Experience developing REST APIs and backend services, particularly Python with FastAPI/Pydantic.
• Experience with Docker, Kubernetes, Helm, cloud infrastructure and orchestration tools such as Airflow or Argo.
• Experience with LLM guardrails, observability, logging and monitoring.
• Experience with SQL and NoSQL databases.
• Desirable: TypeScript, Node.js, Next.js/frontend frameworks.
• Experience working in secure, restricted or air-gapped environments is highly relevant.