Affluent encompasses the financial planning business, Quilter Financial Planning, the Quilter Investment Platform and Quilter Investors, the multi-asset investment solutions business.
High Net Worth includes the discretionary fund management business, Quilter Cheviot, together with Quilter Cheviot Financial Planning.
At Quilter we never stand still. Our foundations are rooted in our extraordinary expertise, which is trusted by hundreds of thousands of customers, but we have great ambitions to stay one step ahead and make an even greater difference to the people and communities we serve.
Our business is transforming, continually modernising, and becoming even more customer centric. So, if you want to be bold in the pursuit of your ambitions, bring new ideas, and challenge and evolve what we do, it’s the perfect time to join us!About the Role
Level: 5
Department: CDO
Location: Southampton or London
Contract type: Permanent
The new role sits within Chief Data Office (CDO) and reports Head of AI. The key accountabilities for the role are as follows:
• AI/ML Solution Delivery: Hands on end-to-end development and deployment of both traditional and GenAI /Agentic AI based machine learning models, including discovery analytics, experimental design, model development, benchmarking, enhancement and deployment.
• Model Design, Prompt Engineering & Evaluation: Design and execute experiments to benchmark and evaluate model performance using both classical metrics (precision, recall, F-score) and GenAI /Agentic AI specific techniques (LLM-as-a-Judge, ROUGE, GANs). Develop and refine prompts to optimize GenAI model reasoning, accuracy, and overall effectiveness.
• Responsible AI: Apply strong understanding of ethical AI principles and governance frameworks, ensuring robust model validation and ongoing monitoring with regulatory and organizational standards.
• Cross-Functional Collaboration: Work closely with business partners, stakeholders, and technical teams to translate business requirements into impactful AI solutions.
• Research & Innovation: Stay abreast of emerging tools, techniques, and best practices in LLMs, RAG, GenAI, Agentic AI model development & evaluation techniques and proactively apply new knowledge to drive innovation.
Qualifications
PhD or MSc in Artificial Intelligence, Machine Learning, Computer Science or a related STEM field.
Knowledge
- Strong foundation in core machine learning algorithms and deep learning concepts (e.g., Neural Nets, CNNs, GANs, RNNs, Transformers).
- In-depth understanding of natural language processing (NLP) model development and large language model (LLM) fine-tuning, evaluation and ongoing monitoring framework
- Deep understanding of prompt engineering techniques, including zero-shot and few-shot prompting strategies with ability to enhance the performance of LLMs and agentic AI systems.
- Solid grasp of data structures and handling for both structured (SQL, pandas) and unstructured (text, images, audio) data, including knowledge bases creation with Graph (Neo4j) and vector stores.
- Demonstrate expertise in designing, building, and deploying AI agents to solve complex business problems.
- Awareness of AI governance, and regulatory considerations, especially in financial services.
Experience
- Proven track record in building, fine-tuning, and evaluating traditional ML, NLP and LLM-based models.
- Hands-on experience with leading ML frameworks (e.g., PyTorch, TensorFlow) and LLM libraries (e.g., Hugging Face, LangChain/LangGraph, LlamaIndex).
- Strong experience in stakeholder management, working closely with business owners, engineers, and governance teams to deliver AI initiatives end‑to‑end
- Experience in GenAI and AI Agent development and deployment using scalable cloud platforms (Azure, AI Foundry, Databricks, AWS).
- Deep expertise in AI model evaluation framework and ongoing monitoring techniques.
- Expertise in provide technical leadership and mentor AI Scientists, supporting their development and ensuring high‑quality AI delivery
- Background in financial services or other regulated industries is highly desirable.
Skills
- Advanced programming skills in Python (and optionally, other languages such as R or Java).
- Strong data engineering and data wrangling abilities for both structured and unstructured data.
- Expertise in model development, evaluation, benchmarking, and continuous improvement.
- Effective communication skills for presenting complex technical concepts to non-technical audiences.
- Problem-solving mindset, curiosity, and a passion for staying up to date with the latest advancements.
- Ability to document work clearly and adhere to best practices in reproducibility and model governance.
#LI-PM1
Inclusion & Diversity
We value diversity and strive to promote inclusivity in all aspects of our culture. We believe in equal opportunities for all, ensuring that no applicant encounters less favourable treatment based on anything but their skills, qualifications, experience, and potential. We celebrate the unique contributions of a diverse workforce and create a respectful, nurturing environment where every colleague can thrive.
Values
Do the right thing: We act with integrity and are proudly committed to going above and beyond in service of our clients and the support we provide our communities.
Always curious: We continuously seek new ideas and knowledge so we’re one step ahead of our clients’ needs. We look for inspiration everywhere and encourage experimentation, recognising that this is how we create brilliant solutions for brighter futures.
Embrace challenge: We aim high to transform our potential into meaningful outcomes. With ambition as our driving force and a steadfast commitment to growth, we succeed for the good of every generation.
Stronger together: Combining our diverse talents, we accomplish more collectively than we ever could do alone. We speak openly, actively listen, and support each other, and constructively challenge and embrace new ideas. We seek empowerment and demonstrate ownership and trust, with the confidence to make impactful decisions.
Core Benefits
Holiday: 182 hours (26 days)
Quilter Incentive Scheme: All employees are eligible to participate in incentive scheme, to incentivise business performance and their contribution.
Pension Scheme: A non-contributory company pension scheme that can be boosted through personal contributions.
Private Medical Insurance: Single cover as standard with options to increase cover to include your partner or children.
Life Assurance: 4x your salary.
Income Protection: 75% of salary, less state benefits, payable after 26 weeks of absence.
Healthcare Cash Plan: Jersey employees only
In addition to our core benefits, we offer a range of flexible benefits to UK employees that you can choose from and pay for conveniently via a salary deduction.
Top Skills
Quilter London, England Office
Senator House, 85 Queen Victoria Street, , England , London, United Kingdom, EC4V 4AB
