Senior AI/ML Engineer – GenAI & RAG

This role is for a client in the investment banking and trading space, supporting Global Business Insights (GBI) to deliver critical metrics and reports to Markets and Securities Services Operations, enabling data-driven decisions across a large, global ecosystem.

• Minimum 7 years of software engineering experience, including at least 3 years delivering production-grade AI/ML pipelines or applications.
• Delivered at least 2 end-to-end AI systems to production, including at least 1 conversational AI/chatbot/assistant/agent solution used by business clients.
• Demonstrated support of live solutions with 5+ production uptime/availability and average response latencies less than 5 seconds under expected load.
• Expert-level Python proficiency with strong software design patterns, automated testing (unit/integration), and cloud-native microservices/API/data pipeline engineering.
• Hands-on containerization and orchestration with Docker and Kubernetes, including production deployment automation with rollback capabilities.
• Real-world experience deploying secure AI architectures on at least one major cloud platform (GCP, AWS, or Microsoft Azure).
• Practical experience across 3+ enterprise-grade LLM families with focus on accuracy, latency, cost, scalability, and security/safety.
• Proven delivery of 2 production-grade RAG systems, including expertise in embeddings, vector databases, hybrid search, reranking, chunking, and optimizing retrieval relevance.

Nice to have:

• Experience building auditable single/multi-agent workflows with frameworks such as LangGraph, LangChain, Google ADK, including human-approval safeguards.
• Experience with additional agent frameworks such as LlamaIndex, Semantic Kernel, AutoGen, or CrewAI.
• Working knowledge of enterprise evaluation and monitoring tooling such as MLflow, Kubeflow, LangSmith, Ragas, or DeepEval.
• Hands-on implementation of AI guardrails including prompt injection/jailbreak detection, content moderation, PII masking, and RBAC.

• Collaborate with business stakeholders to translate requirements into secure, scalable, and compliant AI solutions, owning architecture, development, automated deployment, and post-production support.
• Design, build, and deliver production-grade AI/ML solutions end to end, from concept through deployment and ongoing optimization.
• Develop GenAI experiences including AI assistants, chatbots, agentic workflows, and RAG-based applications.
• Design scalable data, AI, and cloud architectures; build and integrate APIs, frontend/backend services, and enterprise integrations.
• Implement MLOps/LLMOps practices including monitoring, evaluation, guardrails, and continuous improvement for reliability and safety.
• Ensure AI solutions meet security, governance, and compliance requirements, including auditable workflows and human-in-the-loop safeguards.
• Apply advanced engineering for LLM usage such as prompting, function/tool calling, structured outputs, context management, and workflow orchestration.

Only candidates with an existing legal right to work in Europe will be considered for this role.