Forward Deployed Product Engineer, Global Private Equity Technology

The Carlyle Group • Washington, DC

18d • $130,000 - $140,000 • Onsite

About The Position

The Forward Deployed Product Engineer, Global Private Equity Technology is a hands-on engineering role building business-critical applications and applied-AI capabilities for Carlyle’s Global Private Equity (GPE) platform. The Senior Analyst works with stakeholders across Deal Teams, Fund Management, and the broader GPE organization to build solutions that automate workflows and deliver measurable value throughout the investment lifecycle.

The role owns defined features and components end-to-end across backend services, modern frontends, data pipelines, and LLM-based workflows, within technical direction and engineering standards set by senior members of the GPE Product and Engineering organization. It combines technical execution with developing product judgment and direct engagement with business users. Success is measured by business outcomes: understanding user needs, prototyping against real data, delivering production-ready solutions, and supporting adoption.

The position requires working in the office four days per week.

Requirements

• Bachelor’s degree required.
• At least 2 years of overall relevant experience required.
• Experience in software engineering required.
• Hands-on experience building applications using Python required.
• Full-stack application development skills with Python and React and/or Next.js.
• API design and integration across systems and data sources.
• MCP design and integration across systems and data sources.
• Relational databases, SQL, and data pipeline development.
• Applied AI and LLM integration skills, including RAG, prompt design, and agentic workflows.
• Strong written and verbal communication with technical and non-technical audiences.
• Ability to take a defined problem from ambiguity to a working solution with appropriate guidance and raise blockers early.
• Curiosity about the business problem behind requests and comfort asking questions of business users directly.
• Commitment to continuous learning in a fast-moving technical and product environment.

Nice To Haves

• A concentration in computer science, engineering, or a related quantitative field.
• Experience with relational databases and SQL; exposure to enterprise data platforms such as Snowflake, Databricks, or PostgreSQL.
• Frontend development experience with React and/or Next.js.
• Experience building within an agentic harness, including multi-step, tool-using agents with defined scaffolding, orchestration, evaluation, and guardrails.
• Experience with document intelligence, including extracting structured data from unstructured source documents using OCR, layout parsing, or LLM-based extraction from PDFs, agreements, and financial reporting.
• Experience working directly with business users to gather requirements and deliver working software.
• Prior experience in alternative asset management, private equity, financial services, or a startup environment.

Responsibilities

• Build and maintain features and components of business-critical GPE applications through design, implementation, deployment, and ongoing support.
• Develop full-stack functionality using Python on the backend and React and/or Next.js on the frontend.
• Build APIs, services, and data pipelines connecting Snowflake, third-party market and portfolio data, and internal systems.
• Prototype against real data to validate use cases, then help harden successful prototypes into secure, production-grade software.
• Meet team standards for code quality, performance, security, and maintainability.
• Work with Deal Teams, Fund Management, and the broader GPE organization to understand workflows and identify valuable automation opportunities.
• Translate business requests into technical requirements and deliverables, with guidance from senior engineers and product management.
• Support adoption through demos, user enablement, documentation, and follow-up on user feedback.
• Track usage and business impact of delivered solutions and communicate findings to stakeholders.
• Build AI-enabled functionality, including LLM-assisted workflows, intelligent automation, and agentic components, where it provides measurable value.
• Implement RAG pipelines, Knowledge Graph implementations, and other LLM workflows using modern orchestration frameworks and enterprise LLM platforms.
• Connect LLMs to proprietary data using established, permissioned, governed, production-ready patterns.
• Partner with data, platform, and engineering teams to move applied-AI capabilities from proof of concept into production.
• Apply the GPE Product and Engineering organization’s architectural patterns, reusable components, and engineering standards.
• Participate in code reviews and collaborate with teammates on shared deliverables.
• Write technical documentation that makes work transparent, supportable, and reusable across Carlyle Technology.
• Ensure solutions comply with AI governance, data privacy, and information security standards.
• Communicate delivery status, blockers, and technical trade-offs to the team and business stakeholders.

Benefits

• Retirement benefits
• Health insurance
• Life insurance
• Disability insurance
• Paid time off
• Paid holidays
• Family planning benefits
• Wellness programs
• Potential eligibility for an annual discretionary incentive program, dependent on individual and organizational performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level