Applied AI Engineering Lead - VP, Markets Operations

Salary: £62,000 - 102,000 per year Requirements: • Bachelors or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, or related field, or equivalent practical experience • Strong software engineering experience with Python and experience designing, building, and operating production-grade applications • Experience designing and building AI, machine learning, generative AI, or agentic applications, including integration with enterprise systems and workflows • Strong understanding of LLM application patterns, including prompt engineering, retrieval-augmented generation, tool calling, context management, evaluation, and guardrails • Experience with RESTful API design, development, and integration, including frameworks such as FastAPI • Experience with data engineering concepts, ETL and data pipelines, structured and unstructured data, and integration with enterprise data platforms • Experience with CI/CD, automated testing, observability, production monitoring, and operational readiness practices • Familiarity with Infrastructure-as-Code solutions such as Terraform and cloud or container-based deployment patterns • Working knowledge of database design and integration, including relational, document, vector, or graph-based data stores • Understanding of security, controls, compliance, and model risk considerations relevant to enterprise AI systems • Strong verbal and written communication skills, including the ability to influence architecture decisions and work effectively across multidisciplinary teams • Experience designing or operating multi-agent systems, agent orchestration frameworks, workflow automation platforms, or tool-augmented LLM applications • Experience with context engineering techniques, including retrieval strategies, embeddings, vector databases, knowledge graphs, semantic search, memory management, and grounding approaches • Experience building evaluation frameworks for AI applications, including golden datasets, automated scoring, human review workflows, red teaming, regression testing, and production quality monitoring • Experience with continual learning or continuous improvement patterns for AI systems, including feedback loops, telemetry analysis, prompt and model versioning, and experimentation frameworks • Familiarity with Markets Operations processes, trade lifecycle, post-trade operations, reconciliations, controls, exception management, or operational risk • Experience applying Artificial Intelligence in finance, markets, operations, risk, or large-scale enterprise technology environments • Strong presentation, stakeholder partnership, technical leadership, and project execution skills Responsibilities: • Lead the design, development, and implementation of agentic AI applications that support Markets Operations workflows, controls, exception management, and productivity use cases • Define and drive AI engineering architecture patterns for scalable, secure, reusable, and production-ready AI, machine learning, and generative AI solutions • Design and implement agent harnesses, orchestration layers, tool-use frameworks, workflow automation patterns, and guardrails for enterprise AI applications • Develop context management strategies, including retrieval approaches, memory patterns, prompt and context construction, grounding, data access controls, and lifecycle management of contextual information • Build and enhance robust AI services and infrastructure using modern engineering practices, including APIs, event-driven patterns, CI/CD, Infrastructure-as-Code, observability, and automated testing • Partner with AI researchers, data scientists, and software engineers to translate emerging AI capabilities into practical, reliable, and compliant enterprise applications • Establish evaluation, monitoring, and feedback mechanisms for AI systems, including quality measurement, hallucination reduction, regression testing, model performance tracking, and operational risk controls • Design approaches for continual learning and improvement, including human-in-the-loop feedback, telemetry-driven enhancement, model, prompt, and version management, and safe release practices • Collaborate with Markets Operations stakeholders to understand process pain points and translate them into AI-enabled technology solutions with measurable business impact • Document and communicate architecture decisions, design tradeoffs, engineering standards, and implementation patterns to technical and non-technical audiences • Mentor engineers and contribute to a culture of technical excellence, innovation, responsible AI adoption, and continuous learning Technologies: • Agentic AI • AI • API • CI/CD • Cloud • ETL • FastAPI • Support • LLM • Machine Learning • Python • Security • Terraform More: We are a global leader in financial services, providing strategic advice and products to prominent corporations, governments, wealthy individuals, and institutional investors. Our Commercial & Investment Bank is a global leader across banking, markets, securities services, and payments, serving clients in more than 100 countries. We value diversity and inclusion, offer equal opportunity employment, and support reasonable accommodations. This is a full-time role within Markets Operations, and you will work in a collaborative, hands-on environment focused on applied AI innovation, safe and reliable AI adoption, and measurable business impact. last updated 36 week of 2026