We are building the next generation of Large Language Model applications driven by Portfolio Manager requirements that deliver immediate value and scale as a core product.

We are looking for an AI Engineer to lead this work within the Equities Technology AI group. This role will be responsible for designing, expanding, and optimizing the architecture of a strategic, evolving AI platform. The ideal candidate is an experienced engineer who enjoys building and owning high-performance, production-grade AI systems from the ground up.

Responsibilities:

• Understand and translate Portfolio Manager and business problems into robust, production-ready AI solutions.

• Design, build, test, deploy, and own LLM-based products that solve specific Portfolio Manager workflows and generalize into reusable AI capabilities.

• Design and implement agentic AI systems that perform multi-step reasoning, planning, and tool execution.

• Own the end-to-end LLM architecture and lifecycle, including prompt design, model selection, evaluation, deployment, and iteration.

• Identify, design, and implement internal process and infrastructure improvements with a focus on scalability, reliability, and performance.

• Work closely with stakeholders across business and technology organizations to optimize product design and adoption in production environments.

Qualifications:

• PhD in a technical field with 5+ years of industry experience, or Master’s degree with equivalent industry experience.

• Strong Python engineering experience, including object-oriented design, microservices, and REST API development.

• Hands-on experience building and operating production-grade LLM applications.

• Experience with agentic and LLM frameworks.

• Strong understanding of agentic patterns including tool use, planning, memory, and reflection.

• Experience with retrieval-augmented generation, vector databases, and semantic search systems.

• Experience fine-tuning or adapting models using techniques such as LoRA or PEFT.

• Experience developing end-to-end asynchronous applications and distributed systems.

• Experience deploying AI systems in cloud environments such as AWS or GCP.

• Strong interpersonal and communication skills with the ability to operate independently and collaboratively in a fast-paced environment.