Senior AI Engineer

As a Senior AI Engineer at London Stock Exchange Group (LSEG), you will drive end-to-end design, development, and delivery of scalable, secure, high-performance software and AI solutions. You will combine deep engineering expertise with hands-on Large Language Model (LLM) integration, prompt engineering, and engineering leadership.

Software Engineering

• Design and implement complex services and platforms.
• Write clean, maintainable, well-tested code in Java, Python, and other high-level languages.
• Perform performance tuning and root-cause analysis of critical issues.

AI & Machine Learning Leadership

• Design and refine prompt engineering strategies for production LLM applications.
• Integrate, optimize, and evaluate LLMs working with retrieval-augmented generation (RAG), Agentic AI, embeddings, vector databases, and prompt management tools.
• Lead model selection, fine-tuning, and deployment strategies for financial use cases.
• Build and maintain AI evaluation frameworks and automated testing pipelines.

Performance & Reliability

• Champion observability, AI Ops, and real-time monitoring across distributed systems.
• Drive resilience patterns (circuit breakers, retries, graceful degradation) for 99.99% uptime.
• Design cost-effective AI infrastructure optimized for latency and throughput.

Technical Leadership & Mentorship

• Partner with Product, QA, Architecture, Data Science, and Compliance teams.
• Conduct technical design reviews and elevate engineering standards across the organization.
• Mentor senior engineers and lead architectural decisions; model technical excellence.
• Drive technical strategy for AI adoption across multiple product lines.

Innovation & Research

• Track emerging AI/ML frameworks, techniques, and tooling.
• Prototype and assess new approaches for production adoption.
• Build proof-of-concepts that demonstrate business value and technical feasibility.

Quality & Compliance

• Enforce automated testing, CI/CD, and secure coding.
• Advocate for infrastructure-as-code and continuous improvement practices.

Requirements

• 8+ years professional software engineering.
• 1+ year exposure to AI / LLM solution development.
• Proven delivery of complex, high-impact systems.
• Extensive experience in system and application architecture.

Technical Skills

• Languages: Expert in Java and Python; exposure to additional modern languages.
• Architecture: Distributed systems, microservices, API design, event-driven patterns.
• AI / LLM: Prompt engineering, evaluation, fine-tuning, embeddings, RAG, model deployment.
• Data: Vector stores, caching, streaming, persistence strategies.
• Tooling: Prompt management (Langfuse), experimentation frameworks.
• Cloud: AWS, Azure, or GCP (designing secure, scalable workloads).
• DevOps: CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), infrastructure-as-code.
• Security: Identity, secrets management, secure SDLC practices.
• Observability: Metrics, tracing, log aggregation, SLO/SLA design.