Senior Cloud & AI Architect (m/w/d)
Du denkst Systeme ganzheitlich. Von der Idee bis zur skalierbaren Realität. Aufgaben Du entwickelst Cloud- und AI-Architekturen für unsere…
Senior AI Architect - Financial Services London, UK (Hybrid Working Model) Initial 6-Month Engagement £650-£700 per day (Inside IR35) The Opportunity Our client, a leading organisation within the financial services sector, is undertaking a strategic transformation to embed Artificial Intelligence at enterprise scale.
They are seeking a Senior AI Architect to play a pivotal role in shaping, delivering, and-critically-driving the adoption of production-grade AI solutions across the business.
This mandate goes beyond innovation and experimentation. The organisation requires a leader who can translate AI ambition into live, trusted, and widely adopted capabilities, ensuring measurable business impact.
transitioning AI initiatives from proof-of-concept into fully operational, value-generating products. Key ResponsibilitiesAI Strategy & Architecture
Retrieval-Augmented Generation (RAG)
Large Language Model (LLM) integration and orchestration
Agent-based workflows and services
Establish scalable, secure, and reusable AI design patterns aligned to enterprise standards
Product-Focused Delivery
Progress beyond PoC and governance bottlenecks
Are deployed into live environments
Achieve sustained user adoption
Embed a product-centric mindset, with clear ownership of outcomes and value realisation
AI Platform Engineering
RAG pipelines integrating enterprise data sources (e.g., Teams, SharePoint)
Agent-driven applications interfacing with internal and legacy systems
Text-to-SQL solutions enabling natural language interaction with business data
Enable robust deployment through CI/CD-integrated pipelines, including automated workflows within platforms such as Databricks
Technology Leadership (Microsoft Ecosystem)
Azure OpenAI
Azure AI Search
Azure Databricks
Azure AI Foundry
Microsoft Fabric
Define integration standards across AI, data, and enterprise platforms
Adoption, Influence & Investment
Act as a trusted advisor to senior leadership and C-suite stakeholders
Commercial impact
Operational efficiency
Risk mitigation
Build confidence in AI solutions
Unlock and allocate budgets for AI initiatives
Navigate complex stakeholder environments, including resistance to AI investment
Governance & Risk
Ensure all AI solutions adhere to financial services regulatory frameworks, including:
Data privacy and security
Model governance and auditability
Bias mitigation and explainability
Design AI systems suitable for sensitive use cases, such as credit risk, regulatory reporting, and financial data services
Candidate ProfileSector Expertise
Demonstrated experience within banking or regulated financial services environments
Strong understanding of regulatory, risk, and governance frameworks
AI & Engineering Capability
RAG-based knowledge and document intelligence platforms
Natural language data access (e.g., Text-to-SQL)
AI-powered assistants and agent frameworks
Pipelines ingesting collaboration and enterprise content into vectorised indexes
Agent-based front ends for interacting with internal systems
AI solutions supporting regulatory, risk, or financial reporting functions
Technical Expertise
Azure AI ecosystem (Azure OpenAI, AI Search, Databricks, Foundry)
CI/CD-driven AI deployment and pipeline automation
API-led and distributed architectures
Leadership & Influence
Engage and influence senior stakeholders
Translate technical concepts into business-relevant outcomes
Demonstrated ability to drive adoption, not just delivery
Why This Role This engagement offers a rare opportunity to shape how AI is operationalised at scale within a leading financial institution.
The successful candidate will combine deep technical expertise, delivery credibility, and executive influence to ensure AI becomes a core, trusted capability embedded within the organisation.
We welcome conversations with individuals who have a proven track record of delivering AI solutions that are not only technically robust, but actively used, trusted, and delivering measurable value.
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