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LSEG in London seeks an expert Architect to drive technical vision, system design, and governance for a large-scale engineering program spanning multiple domains. You will be the premier technical authority, shaping mission-critical enterprise systems, data ecosystems, and AI integration strategies.
The role requires defining target architecture, establishing patterns for high availability, and guiding security and regulatory compliance in the London financial services context, while partnering
We are seeking an expert Architect to drive the technical vision, system design, and architectural governance for a large-scale, technically diverse engineering program. Operating across multiple complex domains, you will serve as the premier technical authority, designing mission-critical enterprise systems, overarching data ecosystems, and leading our artificial intelligence (AI) integration strategy.
The successful candidate will set the architectural target state, establish design patterns for highly resilient systems, and ensure technical coherence across a highly heterogeneous technology stack. You will partner with business stakeholders and engineering management to translate strategic objectives into robust, scalable, secure, and AI-ready architectures, navigating the complexities of a highly regulated, high-expectation environment.
Define and own the end-to-end target state architecture across diverse systems, data platforms and cloud integrations.
Publish, maintain , and champion architectural blueprints, design patterns, and engineering excellence standards.
Lead the Architecture Review Board (ARB) process for the domain, ensuring technical designs strictly adhere to non-functional requirements (NFRs) such as scalability, maintainability, performance, latency, and security.
AI Architecture Roadmap: Lead the architectural design for integrating AI and Machine Learning capabilities (including Generative AI) into existing and new enterprise products.
AI Governance & Security: Establish secure guardrails, data privacy controls, and ethical compliance standards for AI consumption within a highly regulated environment.
Developer Productivity: Champion the adoption of AI-driven engineering tooling (e.g., AI coding assistants, automated testing generation) to enhance developer velocity and code quality across the portfolio.
Data Readiness: Architect robust, scalable data pipelines ( MLOps / LLMOps ) to support reliable model training, fine-tuning, and low-latency inference.
Act as a senior technical leader and mentor to Principal Engineers and Tech Leads across multiple engineering domains.
Ensure architectural coherence across a diverse technology stack, balancing the need for enterprise standardization with the autonomy of agile delivery teams.
Take ownership of technical debt management strategies and long-term platform health, preventing fragmented or sub-optimal legacy solutions.
Lead technical investigations into complex performance bottlenecks, major systemic incidents, and architectural pivots.
Remain heavily hands-on in the R&D space; write prototype code, execute Proof-of-Concepts ( PoCs ), and directly validate architectural assumptions (specifically around new AI tools or cloud services) before scaling them to development teams.
Collaborate closely with business leadership, product owners, and Development Managers to translate strategic commercial objectives into executable technical roadmaps.
Act as a trusted advisor, articulating complex technical trade-offs, risk mitigation strategies, and system capabilities in clear, business-centric language.
Compute & Services: Java, .NET, Python, Cloud-native