A leading global investment firm with approximately $12bn AUM is building out its next-generation AI capability and is hiring an AI Engineer to define and deliver applied AI systems directly impacting research, trading, and business decision-making.This is a high-visibility role working directly with Portfolio Managers, quants, and senior leadership to architect and deploy production-grade LLM and agentic AI systems across the firm.You will:Define and execute the technical roadmap for firmwide AI initiativesDesign, build, and deploy LLM-powered tools embedded directly into investment workflowsArchitect agentic systems capable of multi-step reasoning, planning, and tool executionBuild and operate MCP (Model Context Protocol) servers to securely connect AI agents to enterprise data and APIsOwn the full LLM lifecycle including prompt and system design, model selection, evaluation, deployment, monitoring, and iterationLead rapid prototyping using RAG, tool and function calling, and modern agent frameworksEstablish best practices for responsible, production-grade AI deploymentMentor engineers and help raise the technical bar across applied AI initiativesThis is not a research-only role. You will be shipping production systems that portfolio managers rely on.What We’re Looking For5+ years of industry experience with the last 2+ years building and deploying production AI systemsAdvanced degree (MS or PhD) in Computer Science, AI, ML, or related quantitative fieldHands-on experience with production LLM applications including evaluation, monitoring, and iterationStrong experience with agentic frameworks and agent design patternsExperience building MCP servers or similar AI integration layersExcellent Python engineering skills including object-oriented design, microservices, and REST APIsAbility to operate independently in a fast-paced, highly collaborative environmentNice to HaveDeep curiosity about AI and emerging technologiesStrong ownership mindset and high ethical standardsExperience delivering AI tools directly to business stakeholdersIf you are excited about building agentic AI systems that directly influence investment decision-making and want to operate at the intersection of AI engineering and capital markets, I would welcome a confidential conversation.