• 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-proof the validation and tooling landscape.• Supporting knowledge sharing, collaboration, and tooling governance across stakeholders.
Requirements
- 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 such as Data Science, Statistics, Mathematics, Computer Science or Physics, or equivalent experience.
- 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 stakeholders.
- To work proactively and independently, manage time effectively, and deliver high-quality outputs within tight timelines.
- Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, Ollama, LlamaIndex, or similar tools; proficiency in SQL.
- Hands-on experience or strong theoretical knowledge of GenAI techniques and methodologies.
- Familiarity with cloud AI platforms such as GCP Vertex AI and BigQuery, Azure AI, or similar enterprise-level AI deployment environments.
- Experience or understanding of frontend development for internal tools or dashboards, with knowledge of TypeScript/JavaScript and modern UI frameworks such as React; familiarity with basic UI/UX principles is desirable, along with an understanding of how AI tooling is consumed by end users.
- Experience or understanding of backend and API development, including designing and consuming RESTful endpoints, integrating services, and supporting end‑to‑end workflows for AI or data-driven applications.
- Experience or knowledge of regulatory requirements and frameworks relevant to AI, such as the EU AI Act, GDPR, SS1/23, and industry best practices in AI ethics and governance.
ATS Optimization KeywordsBelow are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively — a feature exclusive to JobTailor job listings.
Hard Skills
- Python
- SQL
- AI Model Development
- Validation
- GenAI techniques
- PyTorch
- TensorFlow
- LangChain
- Ollama
- LlamaIndex
Soft Skills
- analytical skills
- problem-solving skills
- written communication
- verbal communication
- time management
- proactive work
- independence
- collaboration
- knowledge sharing
- critical evaluation
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