AI Architect

AI Architect

Full-Time 70000 - 90000 £ / year (est.) No working from home possible
LMA Recruitment

At a Glance

  • Tasks: Lead the design and delivery of impactful AI solutions in a dynamic financial services environment.
  • Company: Join a leading financial institution driving AI transformation at scale.
  • Benefits: Competitive daily rate, hybrid working model, and opportunity for significant impact.
  • Other info: Opportunity for career growth and to work with cutting-edge technology.
  • Why this job: Shape the future of AI in finance and drive real business value.
  • Qualifications: Experience in AI engineering and strong communication skills to influence stakeholders.

The predicted salary is between 70000 - 90000 £ per year.

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 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. A key priority is addressing a common industry challenge: transitioning AI initiatives from proof-of-concept into fully operational, value-generating products.

Key Responsibilities

  • AI Strategy Architecture
    • Define and lead the end-to-end AI architecture, encompassing:
    • 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
    • Lead the delivery of production-ready AI solutions, ensuring initiatives:
    • 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
    • Oversee the design and implementation of advanced AI capabilities, including:
    • 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)
    • Operate within a Microsoft-centric technology landscape, including:
    • 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
    • Clearly articulate AI value across:
    • Commercial impact
    • Operational efficiency
    • Risk mitigation
    • Drive enterprise adoption and influence stakeholders to:
    • 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 Profile

  • Sector Expertise
    • Demonstrated experience within banking or regulated financial services environments
    • Strong understanding of regulatory, risk, and governance frameworks
  • AI Engineering Capability
    • Proven track record delivering production AI systems, including:
    • RAG-based knowledge and document intelligence platforms
    • Natural language data access (e.g., Text-to-SQL)
    • AI-powered assistants and agent frameworks
    • Experience delivering solutions such as:
    • 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
    • Hands-on expertise across:
    • Azure AI ecosystem (Azure OpenAI, AI Search, Databricks, Foundry)
    • CI/CD-driven AI deployment and pipeline automation
    • API-led and distributed architectures
  • Leadership Influence
    • Strong communication skills with the ability to:
    • 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.

AI Architect employer: LMA Recruitment

As a leading organisation in the financial services sector, our company offers an exceptional work environment that fosters innovation and collaboration. With a hybrid working model, employees enjoy flexibility while being part of a transformative journey to embed AI at scale. We prioritise professional growth, providing opportunities for continuous learning and leadership development, all within a culture that values trust, accountability, and measurable impact.

LMA Recruitment

Contact Details:

LMA Recruitment Recruitment Team

We think you need these skills to ace AI Architect

AI Architecture
Retrieval-Augmented Generation (RAG)
Large Language Model (LLM) integration
Agent-based workflows
Production-ready AI solutions
CI/CD pipeline automation
Azure AI ecosystem