Lead Applied AI Engineer - Banking Technology, Senior Vice President

Description

The role is a lead AI engineering position in banking technology, covering Investment, Corporate, and Commercial Banking, with the title Senior Vice President.

You will define, design, and deliver large-scale AI solutions across these banking lines, with hands-on technical leadership and ownership of architecture.

The work centres on adopting LLMs, agentic workflows, and generative AI platforms to make operations more efficient, more automated, simpler, and less risky.

You will shape both delivery and the engineering culture around AI, working closely with several technology and business teams.

Responsibilities

• Lead the design, hands-on build, and rollout of scalable agentic and generative AI solutions for high-impact business cases.
• Design agent-based systems covering perception, reasoning, planning, and execution, connecting several LLM providers including OpenAI, Anthropic, and Google.
• Build and ship production-grade full-stack AI applications with current ML and LLM platforms and AI coding tools such as Devin and GitHub Copilot.
• Drive delivery through MVPs, quick iteration, hypothesis testing, and A/B experiments to reach value quickly.
• Set rigorous evaluation frameworks and metrics for AI and agent performance, and keep optimising them against business goals.
• Assess and adopt new AI technologies, especially agent-based and autonomous systems, and act as a thought leader and coach.
• Give front-line technical leadership, guide architecture decisions, and mentor engineers across AI, data, and application teams to build an AI-first engineering culture.
• Make sure every AI solution rests on solid banking domain knowledge and states its business and risk impact clearly, not only its technical merits.

Requirements

• Expert Python and/or Java (Spring Boot), with solid JavaScript or TypeScript (Angular, Node.js).
• Deep understanding of AI fundamentals: knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
• Extensive hands-on work with LLM platforms from OpenAI, Anthropic, and Google, plus RAG pipelines, MCPs, and agent frameworks such as Google ADK.
• Proven results with AI coding tools including Devin, Claude Code, GitHub Copilot, and Antigravity.
• Strong experience with TensorFlow, PyTorch, and data science libraries.
• Track record designing and exposing robust, scalable APIs for AI services.
• Deep knowledge of software engineering practice: system design, CI/CD, testing, resilience, security, and operational stability for AI-driven platforms.
• Strong experience building API-first, microservices, and event-driven systems, including AI data pipelines and their lifecycle management.
• Hands-on use of Docker and Kubernetes.
• Ability to explain complex technical ideas clearly, influence senior stakeholders, and lead high-impact technical discussions.
• Strong grasp of banking and regulated financial environments, and of tying AI capabilities to measurable business results.
• Advanced data science skills, including statistical modelling and experimentation.
• Experience mentoring and growing AI-first engineers while toolchains change quickly.
• Progressive software engineering career with sustained hands-on work.
• Advanced Python skills.
• Dedicated experience with AI, LLM-based systems, and agentic architectures.
• Proven record architecting and delivering several enterprise-scale AI solutions into production.
• Bachelor's or Master's degree in computer science, AI, robotics, or a related quantitative field.

Conditions

Full-time position.

Equal opportunity applies; the company is an equal opportunity employer.