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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 initiatives
- Design, build, and deploy LLM-powered tools embedded directly into investment workflows
- Architect agentic systems capable of multi-step reasoning, planning, and tool execution
- Build and operate MCP (Model Context Protocol) servers to securely connect AI agents to enterprise data and APIs
- Own the full LLM lifecycle including prompt and system design, model selection, evaluation, deployment, monitoring, and iteration
- Lead rapid prototyping using RAG, tool and function calling, and modern agent frameworks
- Establish best practices for responsible, production-grade AI deployment
- Mentor engineers and help raise the technical bar across applied AI initiatives
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This is not a research-only role. You will be shipping production systems that portfolio managers rely on.
What We’re Looking For
- 4+ years of industry experience with the last 2+ years building and deploying production AI systems
- Advanced degree (MS or PhD) in Computer Science, AI, ML, or related quantitative field
- Hands-on experience with production LLM applications including evaluation, monitoring, and iteration
- Strong experience with agentic frameworks and agent design patterns
- Experience building MCP servers or similar AI integration layers
- Excellent Python engineering skills including object-oriented design, microservices, and REST APIs
- Ability to operate independently in a fast-paced, highly collaborative environment
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Nice to Have
- Deep curiosity about AI and emerging technologies
- Strong ownership mindset and high ethical standards
- Experience delivering AI tools directly to business stakeholders
If 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.
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