AlpInvest Forward Deployed Engineer

The Carlyle Group•New York, NY

22d•$190,000 - $220,000

About The Position

Join our dynamic Investment Data Science Team as a Forward Deployed Engineer to partner directly with investment professionals across Primaries, Secondaries, and Co-Investments. This role sits at the intersection of investing, software engineering, artificial intelligence, data, and product development. The successful candidate will work alongside deal teams to understand complex investment workflows, rapidly build technical solutions against real business problems, and transform successful prototypes into scalable products that enhance investment decision-making. Unlike traditional software engineering roles, this position requires the ability to operate as both a hands-on technical builder and a strategic partner to investment professionals. The ideal candidate can move seamlessly between understanding how investors evaluate managers, funds, portfolios, and pricing decisions and designing, building, and deploying the systems that make those workflows faster, more intelligent, and more scalable. This individual will help advance several strategic initiatives, including GP Scoring, One-Day Pricing, AI-powered diligence and research workflows, portfolio and company intelligence, and market signal generation.

Requirements

Bachelor's degree or higher (MS, PhD, MBA, or equivalent), required
8+ years of overall relevant technical experience, required.
Experience in software engineering, forward deployed engineering, applied AI/ML engineering, data-intensive product engineering, or related technical fields, with a proven track record of success.
Strong hands-on programming skills in Python; experience with additional modern application or backend technologies is preferred.
Experience designing, building, and deploying production-grade applications, services, APIs, data products, or AI-enabled systems.
Demonstrated ability to take ambiguous business problems from initial discovery through prototype, deployment, and iteration.
Experience working directly with senior business stakeholders and translating domain-specific needs into technical solutions.
Experience integrating structured and unstructured data from multiple systems into end-to-end workflows.
Familiarity with cloud-based environments, modern data platforms, software development practices, and production system design.
Experience applying generative AI, LLMs, agent-based systems, retrieval systems, or AI-assisted development workflows is strongly preferred.
Experience operating in highly ambiguous environments and managing multiple priorities simultaneously.
Strong product judgment and a demonstrated ability to turn bespoke solutions into reusable, scalable capabilities.

Nice To Haves

Concentrations in Computer Science, Engineering, Data Science, Statistics, Mathematics, Finance, or a related technical or quantitative discipline, preferred.
Experience within private equity, asset management, investment management, alternative investments, financial services, or investment technology is preferred but not required.
Familiarity with investment performance metrics, portfolio analytics, fund structures, manager evaluation, or investment pricing is a plus.

Responsibilities

Embed directly with investment professionals across Primaries, Secondaries, and Co-Investments to understand live investment workflows, pain points, and opportunities for technology to improve decision-making.
Translate ambiguous investment and business problems into technical requirements, rapidly test solutions with users, and iterate based on real-world feedback.
Build applications, services, APIs, data workflows, and AI-enabled tools that integrate directly into the day-to-day investment process.
Own solutions from initial problem discovery and prototyping through production deployment, adoption, and iteration.
Develop a strong understanding of manager selection, fund evaluation, portfolio construction, investment pricing, diligence, and market intelligence workflows.
Transform one-off analyses, prototypes, and manual processes into repeatable, scalable workflows and durable product capabilities.
Develop and enhance the technical systems supporting proprietary GP Scoring, including automated data ingestion, scoring workflows, model integration, and investor-facing experiences.
Contribute to the end-to-end development of One-Day Pricing capabilities for LP interest transactions, connecting document extraction, entity resolution, investment assumptions, GP Score outputs, portfolio data, and pricing algorithms.
Build reusable technical components that can scale across deals, GPs, strategies, and AlpInvest business lines.
Partner with Product, Data Science, Data Engineering, and platform teams to transition successful forward-deployed solutions into supported production products.
Build AI-powered diligence, research, and investment intelligence workflows using LLMs, agents, retrieval systems, and modern application architectures.
Integrate structured and unstructured data across internal and external investment systems to create decision-ready workflows for investors.
Develop reliable orchestration, evaluation, monitoring, and human-in-the-loop patterns for AI-enabled investment applications.
Build solutions across a modern data and application ecosystem, including cloud platforms, APIs, data pipelines, document workflows, and investor-facing applications.
Identify opportunities to automate repetitive processes, reduce manual intervention, and improve the speed and scalability of investment workflows.
Build strong relationships with investment professionals and become a trusted technical partner across business lines.
Work directly with users to uncover underlying needs rather than relying solely on predefined requirements.
Balance speed, technical quality, user experience, and long-term scalability when determining how solutions should evolve.
Communicate technical concepts, tradeoffs, and product decisions clearly to both technical and non-technical stakeholders.
Help drive adoption by ensuring solutions fit naturally into how investment professionals work and make decisions.