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NEXTMOVEFDE careers · United States
The Carlyle Group

Forward Deployed Product Engineer

AI summary of the role

Senior hands-on engineering leader (VP-level) embedded with Carlyle's Global Private Equity deal teams and fund management, owning end-to-end delivery of business-critical applications and applied-AI capabilities.

What you’ll do

  • Own a portfolio of GPE applications end-to-end, from discovery to production and adoption.
  • Build full-stack applications with Python backend and React/Next.js frontend, embedded with deal teams.
  • Develop scalable APIs, services, and data pipelines integrating Snowflake and third-party data (Chronograph, FactSet, PitchBook).
  • Prototype rapidly against real data, then harden winning prototypes into production-grade software.

What you’ll bring

  • Minimum 10 years of relevant software engineering experience with increasing technical scope.
  • Hands-on production experience with Python and enterprise data platforms (Snowflake, Databricks, PostgreSQL, MS SQL).
  • Frontend development experience with React and/or Next.js.
  • Experience developing or integrating production AI applications (LLMs, RAG, orchestration frameworks).

Technologies

Python · React · Next.js · Snowflake · Databricks · PostgreSQL · MS SQL · LangChain · LlamaIndex · AWS Bedrock · Anthropic Claude · RAG

Source and classification

Internal deployment & tooling · Evidence for this classification:

Position Summary The Forward Deployed Product Engineer, Global Private Equity Technology is a senior, hands-on engineering role responsible for building and scaling the business-critical applications and applied-AI capabilities that power Carlyle’s Global Private Equity (GPE) platform. Operating in a forward-deployed model, this Vice President embeds directly with Deal Teams and Fund Management—working alongside the business, learning its workflows firsthand, and shipping working software that measurably improves how deals are sourced, diligenced, executed, monitored, and grown. This is a builder’s leadership role. The Vice President owns a portfolio of products end-to-end—across backend services, modern frontends, data pipelines, and LLM-based workflows—and sets the technical direction, engineering standards, and delivery patterns that the broader GPE Product and Engineering
More from the job description

Position Summary The Forward Deployed Product Engineer, Global Private Equity Technology is a senior, hands-on engineering role responsible for building and scaling the business-critical applications and applied-AI capabilities that power Carlyle’s Global Private Equity (GPE) platform. Operating in a forward-deployed model, this Vice President embeds directly with Deal Teams and Fund Management—working alongside the business, learning its workflows firsthand, and shipping working software that measurably improves how deals are sourced, diligenced, executed, monitored, and grown. This is a builder’s leadership role. The Vice President owns a portfolio of products end-to-end—across backend services, modern frontends, data pipelines, and LLM-based workflows—and sets the technical direction, engineering standards, and delivery patterns that the broader GPE Product and Engineering organization builds on. The ideal candidate pairs deep, current technical execution with sharp product judgment and executive presence, thrives in ambiguous problem spaces, and is energized by turning Carlyle’s proprietary data and domain expertise into scalable, workflow-native capabilities. Unlike a traditional application engineer, the Forward Deployed Product Engineer is measured by business outcomes rather than tickets closed: identifying the highest-value problems, prototyping quickly against real [... source excerpt omitted ...] sign, build, and maintain full-stack applications using Python on the backend and React / Next.js on the frontend, embedded directly with the business rather than working behind a requirements hand-off. Develop scalable APIs, services, and data pipelines that integrate GPE’s enterprise data platform (Snowflake), third-party market and portfolio data (e.g., Chronograph, FactSet, PitchBook), and internal systems. Prototype rapidly against real data to validate use cases in days, then harden winning prototypes into secure, production-grade software. Set and uphold a high bar for code quality, performance, security, and maintainability. Business Partnership & Discovery (20%) Embed w [... source excerpt omitted ...] AWS Bedrock, Anthropic Claude). Design secure, governed patterns for connecting LLMs to proprietary data (e.g., Snowflake accessed via MCP or equivalent), ensuring solutions are production-ready, permissioned, and scalable. Partner with data, platform, and engineering teams to move applied-AI capabilities from proof-of-concept to production. Technical Leadership & Standards (15%) Set technical direction, architectural patterns, and reusable components that the broader GPE Product and Engineering organization builds on. Mentor and provide technical guidance to engineers, product managers, and analysts across the team, raising the overall engineering bar. Provide design input,

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