Solutions Architect

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/XP 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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