Applied AI Engineer

Posted Yesterday
New York, NY, USA
In-Office
Entry level
Professional Services • Consulting
The Role
Build and deploy AI-enabled full-stack applications for financial and analytical users. Responsibilities include integrating LLM features, designing agent orchestration pipelines, developing Python APIs and React interfaces, maintaining ETL pipelines, implementing investment performance and risk calculations, and deploying containerized services with Kubernetes. The role requires practical experience launching customer-facing AI agent products, strong Python and LLM development skills, quantitative or fintech experience, and comfort working with ambiguous requirements.
Summary Generated by Built In

About the company

Our client is a financial technology company.

The role

Raydar is recruiting for this role on behalf of our client. Build and ship AI-enabled software and full-stack applications for demanding business users, partnering closely with them to turn complicated processes into dependable production tools. The work spans backend, frontend, data and AI integration under quick delivery cycles.

What you'll do

- Embed features driven by large language models into client-facing applications, such as natural language search, summarization and automated research helpers.

- Design and implement agent-based pipelines and orchestration layers that link applications to live data sources.

- Develop complete applications, from backend APIs to responsive frontends, shaped around each client's analytical needs.

- Design and maintain performant Python APIs for data access, analytics and model inference.

- Create clear, intuitive React interfaces for exploring complex data.

- Build and maintain dependable ETL pipelines for important market and portfolio data.

- Write calculation layers for performance and risk metrics with Python data libraries.

- Release working software quickly, collect feedback straight from users and refine it in frequent iterations.

- Deploy and run services in containerized client environments with Kubernetes.


Requirements

What we're looking for

- Solid grasp of how AI agents operate internally, plus a proven history of putting agent-based tools to productive use.

- Experience launching customer-facing AI agent products or capabilities from an initial concept to release.

- Deep Python skills, ideally with a web API framework such as FastAPI or Django.

- Hands-on experience building with LLM APIs, agent frameworks, tool integrations and prompt design.

- Background in investing, fintech or another quantitative, data-centric field.

- Ability to make progress where requirements are vague and structure is minimal.

- Real conviction that AI is reshaping software, shown through regular personal use of AI tooling, and a strong curiosity about finance.


Benefits

Compensation and benefits

- Equity

Location and work model

- New York, NY, United States

- Hybrid, 4 days per week in the office

- Full-time

Skills Required

  • Proven experience using AI agents productively
  • Experience launching customer-facing AI agent products or capabilities from concept through release
  • Deep Python programming skills
  • Experience with a web API framework such as FastAPI or Django
  • Hands-on experience with LLM APIs, agent frameworks, tool integrations, and prompt design
  • Background in investing, fintech, or another quantitative, data-centric field
  • Ability to work effectively with vague requirements and minimal structure
  • Regular personal use of AI tools and strong curiosity about finance
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The Company
28 Employees
Year Founded: 2021

What We Do

Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.

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