Tech and Tooling Manager – Markets, AI Modelling

Responsibilities

• You’ll join a dedicated team responsible for the development, implementation, and support of AI/GenAI tooling to enable scalable, efficient, and reliable validation and risk oversight.
• Collaborating to develop tools for validation, testing, explainability, and monitoring.
• Supporting validation activities by developing prototype pipelines and frameworks for testing AI/GenAI models.
• Building and maintaining reusable code libraries to automate model documentation, validation, and risk assessments.
• Driving technical innovation and continuous improvement of the validation tooling environment.
• Developing benchmark testing templates and reporting dashboards to streamline assurance across use cases.
• Monitoring emerging technologies (e.g., LLMOps, RAG pipelines, agent toolkits) to future‑prove the validation and tooling landscape.
• Supporting knowledge sharing, collaboration, and tooling governance across stakeholders.

• 3+ years professional experience working in AI Model Development / Validation, or a similar quantitative role within financial services or other regulated industries; or a recent relevant PhD.
• A numerate degree or equivalent experience (e.g., Data Science, Statistics, Mathematics, Computer Science, or Physics).
• Strong analytical and problem‑solving skills with the ability to critically evaluate complex AI systems and models.
• Excellent written and verbal communication skills, with an ability to communicate complex quantitative concepts clearly to non‑technical customers.
• Ability to work proactively and independently, manage time optimally, and deliver high‑quality outputs within tight timelines.
• Proficiency in Python programming and experience using AI‑specific frameworks or libraries such as PyTorch, Tensor Flow, Lang Chain, Llama Index, or similar tools; including SQL.
• Hands‑on experience or strong theoretical knowledge of GenAI techniques and methodologies.
• Familiarity with cloud AI platforms such as GCP Vertex AI and Big Query, Azure AI, or similar enterprise‑level AI deployment environments.
• Experience and knowledge of regulatory requirements and frameworks relevant to AI, such as the EU AI Act, GDPR, SS1/23, and standard processes in AI ethics and governance.