Product Engineer, Global Credit Technology

The Carlyle Group; New York (NY); On-site; USD 180,000 - 200,000; Full time

Benefits offered by this job

Health insurance

Retirement benefits

Paid time off

Annual discretionary incentive program

Job summary

The Carlyle Group in New York is seeking a skilled Product Engineer for its Global Credit Technology division. The role involves designing and building applications using Python and React, collaborating closely with investment teams to improve credit workflows. Candidates should have a strong software engineering background with at least 8 years of experience, particularly in developing scalable APIs and integrating AI functionalities. The compensation ranges from $180,000 to $200,000, accompanied by comprehensive benefits.

Qualifications

• Minimum of 8 years of overall relevant software engineering experience.
• Hands-on experience building production systems using Python.
• Frontend development experience with React and/or Next.js.
• Experience developing or integrating AI-enabled applications.

Responsibilities

• Design, build, and maintain full-stack applications using Python and React.
• Own features end-to-end, from design to support.
• Work closely with investment teams to understand requirements.
• Create and maintain clear technical documentation.

Skills

Application development

Problem-solving

Communication skills

AI integration

Collaboration

Education

Concentration in computer science or engineering

Master's degree

Tools

Python

React

Next.js

Snowflake

Databricks

PostgreSQL

MS SQL

LangChain

LlamaIndex

Job description

Position Summary

The Product Engineer, Global Credit Technology is a hands‑on engineering role focused on building and scaling business‑critical applications for Carlyle's Global Credit platform. This role partners closely with investment professionals and business stakeholders to design, develop, and deliver high‑quality software solutions that improve credit workflows, analytics, and decision‑making.

This engineer owns features end‑to‑end across backend services, frontend applications, and applied AI capabilities where appropriate. The ideal candidate combines strong technical execution with sound product judgment, is comfortable working in ambiguous problem spaces, and thrives in a business‑embedded engineering model.

Primary Responsibilities

Application Development & Ownership (40%)

• Design, build, and maintain full‑stack applications using Python on the backend and React / Next.js on the frontend
• Own features end‑to‑end, from design and implementation through testing, deployment, and support
• Develop scalable APIs and services that integrate with internal platforms, data sources, and third‑party tools
• Ensure code quality, performance, security, and maintainability through strong engineering practices

Business Partnership & Product Thinking (20%)

• Work closely with Global Credit investment teams and business users to understand workflows, requirements, and pain points
• Translate business needs into clear technical designs and actionable deliverables
• Iterate on solutions based on feedback to drive usability, adoption, and impact
• Build and integrate AI‑enabled functionality into applications where it delivers clear business value
• Develop retrieval‑augmented generation (RAG) pipelines and LLM‑based workflows using tools such as LangChain or LlamaIndex
• Collaborate with data and platform teams to ensure AI solutions are production‑ready, secure, and scalable

Cross‑Functional Collaboration & Offshore Coordination (15%)

• Provide technical guidance and oversight to offshore development teams, including code reviews and design input
• Partner with product managers, data engineers, platform teams, and DevOps to deliver integrated solutions

Documentation & Knowledge Sharing (5%)

• Create and maintain clear technical documentation and architectural artifacts
• Share best practices, reusable components, and learnings across the Carlyle Technology organization

Requirements

Education & Certificates

• Concentration in computer science, engineering, or a related quantitative field, preferred
• Master's degree preferred

Professional Experience

• Minimum of 8 years of overall relevant software engineering experience, required
• Experience with a strong focus on application development, preferred
• Hands‑on experience building production systems using Python, with strong experience working with enterprise data platforms and databases (e.g., Snowflake, Databricks, PostgreSQL, MS SQL)
• Frontend development experience with React and/or Next.js
• Experience developing or integrating AI‑enabled applications, including familiarity with LLMs and orchestration frameworks (e.g., LangChain, LlamaIndex)
• Prior experience or exposure to the alternative asset management or financial services industry, preferred
• Experience working with and coordinating offshore development teams, preferred

Technical & Professional Competencies

• API and service‑oriented architecture
• Experience working with modern data platforms and relational databases
• Applied AI and LLM integration (preferred, not mandatory)
• Strong problem‑solving and communication skills
• Ability to work closely with business users in a fast‑paced, delivery‑focused environment

The compensation range for this role is specific to New York, NY, and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.

The anticipated base salary range for this role is $180,000 to $200,000.

In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.