Lead AI Architect
- Compensation
- Not disclosed
- Location
- London, GB
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Architecture
- Posted
Skills
Nice to have
- Product engineering or AI platform product development experience.
- Experience with Agentic AI frameworks and Model Context Protocol (MCP).
- Knowledge of OpenTelemetry and observability solutions for AI workloads.
- Exposure to Responsible AI frameworks and AI governance regulations.
- Consulting and client-facing delivery experience within global organizations.
- Public speaking, thought leadership, blogging, or technical publication experience.
- Financial Services domain certifications or cloud architecture certifications.
Full description
Job Title: Lead AI Architect - Financial Services
Location: London
About the Job you are considering:
**we are seeking a highly experienced Lead AI Architect to drive the design, architecture, and deployment of enterprise-scale AI solutions within regulated financial services environments. This role will combine strategic architecture leadership with hands-on technical delivery, helping clients transition AI initiatives from proof-of-concept to robust, scalable, and governed production solutions.
The successful candidate will define reusable AI engineering foundations, establish architecture standards, and lead complex client engagements across Banking, Insurance, and Capital Markets. They will work closely with engineering, data, risk, compliance, and executive stakeholders to ensure AI systems are explainable, secure, cost-effective, and compliant with regulatory expectations.
Hybrid working:
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
**Your Role:
AI Solution Architecture & Delivery**
- Lead the architecture, design, and implementation of enterprise AI and Generative AI solutions within regulated financial services organizations.
- Partner with client engineering, data, security, and risk teams to operationalize AI solutions and move them into production environments.
- Define end-to-end AI architecture covering data ingestion, retrieval, orchestration, model serving, governance, and monitoring.
- Design scalable AI/ML platforms leveraging cloud-native services and modern data architectures.
- Ensure AI solutions operate within agreed governance, security, and compliance frameworks.
- Conduct architecture reviews and provide technical leadership throughout project lifecycle.
- Lead technical workshops, demonstrations, and architecture discussions with CIOs, CTOs, CDOs, Risk Leaders, and Engineering Teams.
Data, Context & Control Architecture
- Design robust data foundations supporting AI workloads, including semantic layers, knowledge graphs, vector databases, and retrieval systems.
- Establish architectures that ensure AI models leverage trusted and governed enterprise data.
- Define data lineage, traceability, and auditability requirements for AI-driven business processes.