Senior AI Engineer Role Overview

The Senior AI Engineer is responsible for designing, building, deploying, and maintaining advanced AI and machine-learning systems, with a strong focus on cloud platforms and modern, scalable architectures. This role leads the full lifecycle of AI products from solution design and feature engineering to model development, deployment, monitoring, governance, and optimisation.

The position plays a key role in delivering predictive analytics solutions across clients, partnering closely with business stakeholders, data engineers and subject matter experts.

Key Responsibilities:

• Lead end-to-end AI product development, including design, feature engineering, model building, deployment, monitoring, and continuous optimisation.

• Identify and test innovative data science techniques for predictive analytics use cases in healthcare.

• Assist with research on emerging Data Science and AI trends, specifically for healthcare applications.

• Engage business stakeholders during discovery to identify problems/opportunities, gather requirements, and define expected modelling outcomes.

• Partner with stakeholders to shape approaches to key business challenges and contribute to new business strategies.

• Develop conceptual designs and models to address business requirements.

• Collaborate with subject matter experts to select relevant data sources and ensure solutions align with business needs.

• Work closely with the Data Engineering team to acquire internal and external data and manage data utilisation.

• Support governance, model monitoring, and operational excellence in production environments.

Qualifications:

• Degree (Honours, Master’s, or PhD) in Statistics, Computer Science, Engineering, Mathematics, or a related quantitative field.

• Relevant Data Science or AI certifications (e.g., Python, cloud platforms, big data, machine learning, or cloud infrastructure such as Microsoft, Amazon Web Services, or Apache Hadoop).

Required Experience:

• 7–10+ years of hands-on experience in applied machine learning or AI engineering.

• Strong experience with Databricks, MLflow, classical ML, and LLM operationalisation.

• Advanced proficiency in Python and SQL.

• Solid experience with big data systems and cloud-based production environments.

• Proven ability to translate business problems into scalable AI solutions.

Key Skills & Attributes

• Deep understanding of modern AI/ML architectures and cloud-native deployments.

• Strong stakeholder engagement and communication skills.

• Ability to work across multidisciplinary teams (business, engineering, and analytics).

• Strategic thinker with a practical, delivery-focused mindset.

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"If you have not heard from us in two weeks, please note that you were unsuccessful for the role. However, we will keep your resume on file and reach out if any other suitable opportunity arises in the future