in fast-paced, lean, Agile/DevOps environments Broad architectural understanding across enterprise, networks, data, and security domains Experience working across both AWS and Azure cloud environments (S3, Redshift, Athena, Glue, MSK, Entra ID, Azure SQL, Data Factory, Integration Services) Strong integration and API expertise (including REST) Proven ability to produce detailed high-level and low-level design documentation More ❯
on scenario training into our cyber security apprenticeships. The Project Ares platform offers a totally immersive experience, using automated features to support skills adoption with an in-game advisor, Athena, who advises our players through scenario-based challenges. The platform scenarios replicate the unpredictability and escalating levels of complexity that cyberattacks can present. It drives high levels of engagement More ❯
agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure-as-code tools like AWS CloudFormation and Terraform … evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda, Athena/Redshift, etc.) is expected. Strong knowledge of DevOps/ More ❯
