Solution Architect – Generative AI - Fintech
Location: London
I’m currently partnering with an innovative Financial Services business that is building cutting‑edge Generative AI platforms for enterprise clients. They are looking for a Solution Architect who can bridge deep technical expertise with client‑facing advisory skills to deliver scalable, secure AI solutions.
This is a fantastic opportunity to work at the forefront of LLMs, enterprise AI architecture, and cloud‑native systems, helping organisations deploy real‑world GenAI applications at scale.
The Role
As a Solution Architect, you will play a pivotal role in designing and delivering advanced Generative AI solutions for enterprise customers. You’ll collaborate with engineering, product, and business teams to architect robust systems while advising clients on the best ways to deploy AI within complex environments.
You’ll also act as a technical leader across client engagements, shaping solution design, ensuring security and compliance, and influencing the evolution of the company’s AI platform.
What You’ll Be Doing
- Architect and implement enterprise Generative AI solutions using LLMs, RAG pipelines, prompt engineering and frameworks such as LangChain
- Design scalable AI systems using Azure OpenAI, OpenAI API, Claude, Bedrock or Vertex AI
- Lead the architecture of secure, production‑ready solutions across cloud and distributed environments
- Act as a trusted technical advisor to clients, guiding deployment and integration into existing systems
- Produce architecture documentation, diagrams and technical design artefacts
- Mentor delivery teams and support successful implementation across complex projects
- Influence the product roadmap based on real‑world deployment needs and evolving AI trends
What They’re Looking For
- Experience as a Solution Architect, Software Architect, AI Architect, or Enterprise Architect
- Strong background in cloud platforms (AWS, Azure, or GCP)
- Previous experience in a Fintech / Payments environment
- Knowledge of Generative AI technologies, LLMs, RAG architectures, and ML deployment
- Familiarity with DevOps, CI/CD, and infrastructure as code
- Strong understanding of security architecture and enterprise system integration
- Excellent client‑facing and stakeholder communication skills
- Nice to have: Kubernetes, containerisation, microservices architecture
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