The Solution Architect & AI Manager will bridge the gap between complex data architecture and cutting-edge AI implementation. You will be responsible for the strategic delivery of the AIPX framework within the Balance Sheet Management (BSM) domain, ensuring that AI-driven insights are built on a foundation of robust, scalable, and high-performance engineering.
Key Responsibilities
- Lead cross-functional engineering teams to design, build, and deliver data-intensive platforms and AI-powered solutions aligned to strategic business needs.
- Oversee end-to-end delivery across the data and AI lifecycle for Balance Sheet Management (BSM)-from data ingestion and modelling through to ML model development, deployment, and ongoing monitoring.
- Act as the AIPX Delivery Manager by leading the design and build of robust data pipelines and the creation of high-quality derived data products, ensuring alignment with AIPX architecture, performance standards, and business consumption needs.
- Provide strong technical direction across data architecture, cloud engineering, and AI/ML capabilities to ensure scalable, secure, and well-governed solutions.
- Collaborate with product owners, data teams, and business stakeholders to prioritise backlogs, manage risks, and translate requirements into actionable technical plans.
- Establish and enforce engineering best practices-including coding standards, DevOps/MLOps pipelines, testing frameworks, and documentation-to ensure high-quality delivery.
- Drive innovation by evaluating emerging data and AI technologies, leading proofs of concept, and embedding responsible AI principles across all project work.
- Maintain strong knowledge of big application development and demonstrate an ability to work effectively across the various tech teams of the bank.
Knowledge / Experience Required
- Strong knowledge of AI techniques and approaches, with a proven track record of successfully applying AI in previous professional roles.
- Expertise in AI tools and frameworks to accelerate delivery from “idea to value”.
- Deep understanding of Gen AI models/LLMs, with the ability to ascertain and justify which models to apply to particular financial use-cases.
- Experience in following best-practice delivery and production support within a highly regulated organization.
- Proven experience running fast-paced delivery teams with close alignment to business functions and stakeholder requirements.
- Knowledge of Agentic Workflow/orchestration is considered a distinct advantage.
- Familiarity with spec-driven development and new AI engineering practices to deliver an automated SDLC is an advantage.
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