AI Lead Data & AI Enablement Lead

We are looking for an experienced AI Lead / Data and Artificial Intelligence Enablement Lead to identify high-value artificial intelligence opportunities recommend suitable solution approaches and enable data and engineering teams to adopt artificial intelligence capabilities.

The role involves working across generative artificial intelligence retrieval-augmented generation artificial intelligence agents traditional machine learning predictive modelling and intelligent automation. The candidate will be responsible for converting business opportunities into secure scalable measurable and production-ready solutions.

• Partner with business data and technology teams to identify and prioritise artificial intelligence use cases.
  

• Evaluate whether rules analytics traditional machine learning retrieval-augmented generation generative artificial intelligence or automation is the most suitable solution.
  

• Define artificial intelligence architectures technology selections delivery approaches and implementation roadmaps.
  

• Lead the design and delivery of retrieval-augmented generation solutions including document processing chunking embeddings vector search retrieval re-ranking and grounded response generation.
  

• Guide predictive modelling initiatives involving classification regression forecasting anomaly detection recommendations and optimization.
  

• Assess managed models open-source models fine-tuning approaches and custom modelling solutions.
  

• Develop secure integrations between artificial intelligence services enterprise data platforms applications and business workflows.
  

• Establish evaluation frameworks to measure model quality retrieval relevance hallucination accuracy latency cost and business value.
  

• Significant experience delivering artificial intelligence machine learning or advanced analytics solutions in production environments.
  

• Strong understanding of the complete artificial intelligence lifecycle from problem definition and data preparation to evaluation deployment and monitoring.
  

• Practical experience implementing retrieval-augmented generation solutions.
  

• Strong knowledge of large language models embeddings vector databases retrieval re-ranking prompt engineering and model evaluation.
  

• Strong programming skills in Python and SQL.
  

• Experience with common data science and machine learning libraries.
  

• Knowledge of modern cloud data platforms such as Snowflake and Databricks.
  

• Experience developing structured semi-structured and unstructured data pipelines.
  

• Experience integrating artificial intelligence solutions through application programming interfaces applications and enterprise workflows.
  

• Knowledge of machine learning operations large language model operations continuous integration and continuous delivery experiment tracking model registries and production monitoring.
  

• Professional growth and career development in artificial intelligence and machine learning.
  

• Opportunities to work on generative artificial intelligence predictive modeling and intelligent automation solutions.
  

• Exposure to artificial intelligence architecture experimentation and production implementation.
  

• Collaboration with business data engineering and technology teams.
  

• Opportunity to develop reusable artificial intelligence architectures frameworks and engineering patterns.
  

• Experience in responsible artificial intelligence governance security and regulatory compliance.
  

• Opportunities to coach teams and build organizational artificial intelligence capabilities.
  

• Exposure to modern cloud data platforms and enterprise artificial intelligence technologies.