AI Engineer, LLM, MCP, Gen AI

AI Engineer About the Role

An elite midsized hedge fund is looking for an experienced AI Engineer to help design and deliver intelligent applications that leverage modern large language models, machine learning, and automation technologies. This role will partner with technical and business stakeholders to build scalable AI solutions that improve internal workflows, enhance productivity, and enable data-driven decision-making.

Key Responsibilities

• Architect, build, and deploy AI-powered applications utilizing large language models (LLMs), machine learning, and intelligent automation.
• Develop conversational AI solutions, AI assistants, copilots, and workflow automation tools for internal users.
• Design and implement Retrieval-Augmented Generation (RAG) systems, Model Context Protocol (MCP) integrations, function-calling capabilities, and connections to enterprise data sources and APIs.
• Build, test, and maintain production-ready AI services and backend components using Python.
• Evaluate emerging AI frameworks, models, and technologies, developing prototypes and transitioning successful concepts into production.
• Collaborate with engineering, data, and business teams to identify opportunities where AI can create measurable business value.
• Optimize AI applications for scalability, reliability, security, and performance.
• Stay current on advancements in generative AI, agentic AI, and machine learning technologies to continuously improve existing solutions.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical discipline.
• 5\+ years of professional software engineering or AI/ML development experience.
• Strong proficiency in Python and experience developing production-quality applications.
• Experience building applications using modern LLM frameworks such as LangChain, LlamaIndex, or similar technologies.
• Familiarity with vector databases, embeddings, prompt engineering, and retrieval-based AI architectures.
• Experience integrating commercial or open-source LLMs through APIs (e.g., OpenAI, Anthropic, or comparable providers).
• Hands-on experience implementing MCP, agentic AI workflows, or AI orchestration frameworks is highly desirable.
• Ability to integrate AI solutions with databases, APIs, and enterprise systems.
• Experience within financial services, capital markets, asset management, or other highly regulated industries is a plus.