LLM EngineerseniorLondon Area, United KingdomonsitefulltimeInvestment Banking and BankingLLMsAgentic AIRAGPythonC++LangChainVector databasesPrompt engineeringposted 07 Jul
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AI Engineer — Agentic AI Applications
FMX is seeking an experienced AI Engineer to help design, build, and scale AI-powered applications for our rates and derivatives exchange business. This role is ideal for an engineer with strong software development experience, hands-on expertise with large language models, and practical experience building agentic AI systems that can reason, use tools, retrieve information, orchestrate workflows, and operate reliably in production environments.
The ideal candidate will bring a strong engineering foundation, a deep understanding of LLM behavior and failure modes, and experience developing AI applications that meet high standards for reliability, security, observability, and responsible use. You will work closely with product, engineering, data, and business stakeholders to deliver AI solutions that support FMX’s exchange technology, market operations, analytics, and business workflows.
Responsibilities
Design, build, evaluate, and maintain production-grade AI-powered applications that support FMX’s rates and derivatives exchange business.
Develop agentic AI workflows that leverage LLMs, retrieval systems, tool use, planning, orchestration, memory, and structured outputs.
Architect reliable AI application patterns, including human-in-the-loop controls, escalation paths, guardrails, monitoring, and fallback mechanisms.
Evaluate LLM- and agent-powered systems using quantitative and qualitative methods, including benchmark design, red-team testing, regression testing, failure analysis, and success metric definition.
Analyze model behavior, identify failure modes, and implement improvements related to accuracy, reliability, latency, cost, safety, and user experience.
Build and integrate APIs, data pipelines, vector databases, search systems, workflow engines, and internal systems to support AI application development.
Apply software engineering best practices, including clean architecture, automated testing, CI/CD, logging, monitoring, documentation, and operational support.
Partner with cross-functional teams to translate FMX business needs into technical designs and deliver scalable AI solutions.
Contribute to technical strategy and architectural decisions for AI platforms, reusable components, evaluation frameworks, and deployment patterns.
Mentor other engineers in the FMX Development team and help raise the team’s AI engineering capabilities.
Stay current with advances in LLMs, agentic AI frameworks, evaluation methods, AI application architecture, and emerging best practices.
Qualifications
Bachelor’s degree in computer science, machine learning, mathematics, engineering, or a related technical field.
5+ years of professional software engineering experience, including experience building and supporting production systems.
2+ years of hands-on experience developing AI, machine learning, or LLM-powered applications.
Demonstrated experience building agentic AI systems, including tool-using agents, multi-step workflows, retrieval-augmented generation, orchestration patterns, or autonomous/semi-autonomous task execution.
Strong programming skills, with fluency in C++ and Python, and experience writing clear, tested, maintainable, production-quality code.
Experience with modern LLM development patterns, including prompt engineering, structured outputs, function/tool calling, RAG, embeddings, vector search, model evaluation, and hallucination mitigation.
Practical understanding of LLM failure modes, including hallucinations, prompt injection, data leakage, tool misuse, reasoning errors, bias, and non-deterministic behavior.
Experience designing evaluation frameworks for AI applications, including test datasets, scoring methods, human review workflows, regression testing, and performance monitoring.
Hands-on experience with APIs, microservices, data integration, cloud deployment, observability, automated testing, and CI/CD.
Strong understanding of security, privacy, access control, and responsible AI considerations, especially in enterprise environments.
Ability to communicate complex technical concepts clearly to engineering, product, and business stakeholders.
Proven ability to operate independently, make sound technical decisions, and guide projects from concept through production deployment.
Preferred Qualifications
Experience applying AI in financial markets, exchanges, trading platforms, rates, derivatives, clearing, market data, risk, or other capital markets environments.
2–4 years of hands-on experience with agentic AI frameworks and orchestration tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
Experience with vector databases and search technologies such as Pinecone, Weaviate, Milvus, FAISS, OpenSearch, Elasticsearch, or pgvector.
Experience with model monitoring, AI observability, evaluation platforms, or LLMOps tools.
Experience designing human-in-the-loop review systems, approval workflows, or controls for high-impact AI use cases.
Knowledge of model governance, auditability, explainability, and risk management practices.
Experience mentoring engineers, leading technical design discussions, or contributing to AI platform strategy.
Graduate degree in computer science, machine learning, artificial intelligence, statistics, mathematics, or a related field.
Key Attributes
Strong ownership mindset and ability to deliver production-ready solutions for a mission-critical exchange environment.
Pragmatic approach to AI engineering, balancing innovation with reliability, safety, and business value.
Curiosity about model behavior and a rigorous approach to testing, evaluation, and continuous improvement.
Comfort working in ambiguity and translating emerging AI capabilities into practical applications for FMX.
Collaborative mindset with the ability to influence technical and non-technical stakeholders across the FMX business.