Applied AI Engineer

Applied AI Engineer - London - Up to £190,000 - Permanent

A rare opportunity has risen for a Senior Applied AI Engineer to join a dedicated team at the heart of a leading global financial organisation's AI function.

As a Senior Full Stack Applied AI Engineer, you will be responsible for designing, building and deploying innovative AI-powered applications across the full technology stack. You'll combine hands-on software engineering expertise with deep knowledge of modern AI frameworks, LLMs and agent technologies.

The Role

Translate business challenges and problem statements into working proofs of concept and production-grade AI solutions. Architect, develop and deploy AI-native applications leveraging Large Language Models (LLMs), agentic systems and multimodal AI technologies. Design, build and orchestrate intelligent agent workflows using the Gemini Enterprise Agent Platform, Agent Development Kit (ADK) and Agent2Agent (A2A) protocol. Develop and implement Retrieval-Augmented Generation (RAG) architectures, vector search capabilities and long-term agent memory solutions. Deploy, monitor and improve AI agents using Google's managed agent runtime and foundation models, including Gemini and Claude. Create intuitive, scalable user interfaces using modern front-end technologies such as React, Next.js and Svelte. Build robust backend services, APIs and orchestration frameworks to support AI-powered applications. Design and manage data architectures across SQL, NoSQL and vector database environments. Collaborate with business stakeholders to identify, prioritise and deliver AI use cases that generate measurable business value. Assess AI platforms, models and third-party technologies against criteria including performance, scalability, cost, latency, security and maintainability. Conduct model benchmarking, technical due diligence and framework evaluations to inform technology decisions.

Skills & Experience

Demonstrated experience designing, developing and deploying Applied AI and Generative AI solutions in production environments. Strong hands-on expertise with Large Language Models (LLMs), AI agents and modern orchestration frameworks. Experience working with Google Cloud AI services, particularly Gemini-based technologies and ecosystems. Advanced Python development skills, with exposure to TypeScript considered highly advantageous. Full-stack software engineering experience, with a strong emphasis on backend development, distributed systems and API design. Hands-on experience building applications using React, Next.js, Svelte or comparable modern front-end frameworks. Strong understanding of SQL, NoSQL and vector database technologies, including platforms such as PostgreSQL and Firestore. Proven experience implementing RAG architectures, prompt engineering techniques and AI model evaluation methodologies. Practical experience with containerisation and cloud-native technologies, including Docker, Kubernetes, CI/CD pipelines and Infrastructure as Code (IaC) tools such as Terraform. Strong problem-solving, stakeholder engagement and architectural design skills, with the ability to translate business requirements into scalable AI solutions.