AI Engineer, Investment Research

About WisdomTree

WisdomTree is a global asset manager focused on innovation across ETFs, digital assets and next-generation investment solutions. Our Investment Research team works across markets, portfolio construction, quantitative research, product development and client-facing market intelligence.

We are building a new generation of research technology that combines investment expertise, data, modern software engineering and AI.

The Opportunity

We are looking for a hands-on AI Engineer with 0-3 years experience to join our Investment Research team.

We are looking for someone who is productive with modern AI coding tools, but who also has the software engineering fundamentals to understand, maintain and improve the systems those tools help create.

A major initial responsibility will be taking ownership of RAPID, WisdomTree's internal platform for rapidly building and deploying research applications. RAPID allows researchers and investment professionals to turn ideas into working web applications using modern AI-assisted development techniques.

The platform has grown quickly, which is a good problem to have. Your job will be to take what works, keep the speed and experimentation that made it successful, and progressively make the underlying platform simpler, more robust and easier for other developers to understand and operate.

You should be equally comfortable using an AI coding agent to build an application in an afternoon and opening the resulting codebase to work out how it actually works.

What You Will Do

• Own and evolve the RAPID platform, becoming the primary developer responsible for its architecture, codebase, developer experience, reliability and ongoing operation.
• Work directly with researchers, portfolio strategists and senior investment professionals to turn loosely defined ideas into useful applications quickly.
• Use modern AI coding tools and agents extensively to prototype, build, debug and refactor software.
• Take AI-generated or rapidly prototyped applications and apply sound engineering judgment so they remain understandable, maintainable and supportable.
• Simplify RAPID's development environment and container architecture, particularly the local developer experience, removing unnecessary complexity where possible.
• Improve development and deployment workflows including containers, CI/CD, environment management, logging, monitoring, authentication and configuration.
• Build full-stack research applications using Python and modern web technologies.
• Develop applications that combine LLMs with structured financial data, market data, proprietary research, documents and internal knowledge.
• Build agentic workflows, research assistants, analytical tools, dashboards and workflow automations.
• Integrate applications with WisdomTree's data and technology platforms, including Databricks, databases, APIs, identity systems and cloud infrastructure.
• Debug unfamiliar systems pragmatically. You should be comfortable tracing a problem across application code, containers, APIs, authentication, networking and cloud infrastructure rather than assuming somebody else owns the next layer.
• Establish sensible engineering standards without introducing heavyweight processes that slow down experimentation.
• Document important architectural decisions, dependencies and operational procedures so that knowledge does not live with one developer.

What We Are Looking For

The most important requirement is an unusual combination: you know how to move extremely quickly with AI-assisted development, but you also know what good software looks like.

You should have:

• Strong software engineering fundamentals and substantial hands-on development experience.
• Strong Python skills and experience building real applications rather than only notebooks or analytical scripts.
• Experience with modern web development. React, TypeScript or JavaScript experience is strongly preferred.
• Significant experience using AI coding agents and copilots as part of your normal development workflow.
• Experience building applications using LLMs, agents, tool calling, retrieval or related AI application patterns.
• Strong practical knowledge of APIs, Git, containers and Docker.
• Experience with cloud-hosted applications and CI/CD. Azure experience is useful but not essential.
• A working understanding of authentication, application security, secrets, networking, logging and observability.
• The ability to read an unfamiliar or imperfect codebase, understand why it works and improve it without feeling compelled to rewrite everything.
• Good architectural judgment, particularly the instinct to simplify systems rather than add unnecessary abstraction.
• The ability to work independently with ambiguous requirements and a strong bias toward shipping something useful.
• Strong communication skills and the ability to work directly with investment professionals who may know exactly what they want to achieve but not how the software should be constructed.

Particularly Interesting to Us

We would be especially interested if you have experience with some of the following:

• Databricks, Spark or modern cloud data platforms.
• SQL and large financial or analytical datasets.
• Docker Compose, development containers or improving complex local development environments.
• Azure App Services or similar managed application platforms.
• LLM evaluation, retrieval-augmented generation and agent frameworks.
• Building internal developer platforms or self-service application environments.
• Quantitative finance, investment research, portfolio analytics, ETFs or financial markets.
• Taking an experimental or founder-built codebase and maturing it without destroying the qualities that made it useful.

How We Think About Development

We are enthusiastic users of AI-assisted development.

We do not measure engineering ability by how many lines of code someone types manually. If an AI coding agent can do something effectively, we expect you to use it.

But speed does not eliminate the need for engineering judgment.

You need to know when generated code is good, when it is wrong, when the architecture is becoming unnecessarily complicated, and when a prototype needs to be hardened before other people depend on it.

The ideal candidate therefore sits somewhere between a strong product engineer, an AI power user and an entrepreneurial builder.

We want someone who can vibe code their way to a working solution, then engineer it well enough that somebody else can safely own it.

Background

A bachelor's or master's degree in Computer Science, Mathematics, Engineering, Physics, Statistics, Finance or another quantitative discipline would be useful, but we care considerably more about what you have built and your ability to demonstrate strong technical judgment.

An interest in financial markets and investing is important. Deep financial expertise is not required on day one, but curiosity and the ability to learn quickly are.