Applied AI Engineer

Join us as an Applied AI Engineer

• Step into a full-stack engineering role where you’ll design, fine-tune, and integrate generative AI (GenAI) models into scalable, production-grade systems
• You’ll drive improvements across the GenAI platform and shared tooling, accelerating how the bank builds, deploys and scales AI solutions
• You’ll work at the forefront of GenAI engineering, applying emerging techniques to build innovative systems that push the boundaries of what’s possible
  
  

What you’ll do

As our Applied AI Engineer, you’ll design, build, and productionise cutting edge GenAI solutions within the bank. You’ll take end-to-end ownership, from selecting the right architecture and approach through to delivering robust, secure, and scalable systems that operate reliably in production environments.

You’ll engineer advanced retrieval‑augmented generation, agentic, and orchestration systems over enterprise data, making informed decisions on patterns, tools, and trade‑offs. Alongside this, you’ll develop and optimise training, fine‑tuning, and inference pipelines, so our solutions are performant, cost‑efficient, and production‑ready. You’ll also apply the latest machine learning (ML) advancements to design and deploy innovative algorithms and models, so research turns into practical, real‑world capabilities that drive meaningful impact across the organisation.

Your Work Will Focus On

• Building data tooling and infrastructure for multimodal datasets at scale, including text, documents, and audio and visual data, to support robust GenAI use cases
• Deploying solutions through the bank's CI/CD, security, and change-control frameworks, so systems are compliant and resilient
• Monitoring and maintaining production models, tracking drift, latency, cost, and failure, and leading incident response for stability and performance
• Implementing controls for model risk, data governance, and regulatory requirements, embedding these into live systems to support safe AI deployment

Producing high-quality documentation of research and development outcomes for transparency, knowledge sharing, and alignment with ethical and regulatory standards

The skills you'll need

Be the hands-on GenAI engineer who can design, build and scale real-world solutions with strong engineering discipline, delivering measurable impact in real-world systems. To succeed in this role, you’ll bring strong software and ML engineering experience in production environments, with the ability to design practical GenAI solutions from complex business problems.

You’ll be highly proficient in Python and modern ML frameworks such as PyTorch or TensorFlow, with hands‑on experience building and operating training and inference pipelines. You’ll also demonstrate strong engineering discipline, applying best practices in testing, observability, scalability and security to deliver reliable systems.

You’ll Need

• A strong understanding of GenAI architectures from a systems perspective, enabling you to design robust and efficient solutions
• Experience deploying and operating ML systems in cloud or regulated environments
• The ability to collaborate effectively across teams, working closely with scientists, product and platform partners to deliver end‑to‑end solutions
• Familiarity with vector databases, retrieval systems and embedding pipelines
• Experience operating GenAI systems at scale, applying LLMOps or MLOps principles to deliver high‑performance solutions