Engineer, AI & Process Automation
The Carlyle Group
Software Engineering, Data Science
Washington, USA
USD 160k-180k / year
Position Summary
Responsibilities
- Embed with business stakeholders to scope and ship AI and automation products that change how Carlyle works.
- Own delivery on the products you build: discovery, requirements, build, deployment, adoption, and iteration, in partnership with your manager and the rest of the team.
- Build AI native applications including agentic workflows, LLM powered analytics, document intelligence pipelines, and human in the loop copilots that turn data into decisions.
- Automate high-volume Corporate Services processes end to end — from intake and data capture through approvals, exceptions, and downstream systems — retiring manual work and freeing teams to focus on higher-value judgment.
- Move at the speed required to keep AI at the leading edge: prototype in days, harden in weeks, and operate at firm scale.
- Partner deeply with users in their environment so that what you ship is what they actually use, not what they asked for in a kickoff meeting.
- Write production quality code and apply rigorous engineering practice: code review, testing, deployment hygiene, monitoring, and incremental hardening of high stakes systems.
- Use modern AI coding agents and developer tools (Claude Code, Cursor) and the surrounding DevOps stack effectively to deliver faster without sacrificing quality.
- Build within the team’s standards, patterns, and guardrails for AI solutions, and contribute back improvements as you discover them.
- Contribute reusable building blocks (components, evaluation harnesses, prompt and agent patterns, deployment templates) so each new use case starts further down the field than the last.
- Partner with infrastructure, data, and security teams to ensure what you ship deploys cleanly into Carlyle’s environment and meets enterprise standards for observability, controls, and audit.
- Stay current on the AI landscape and bring promising tools, models, and techniques to your manager and the team for evaluation.
Qualifications
- Bachelor’s degree, required
- Concentration in computer science, software engineering, mathematics, physics, data science, or a related technical field, preferred
- Master’s degree, preferred
- 5+ years of overall relevant hands on engineering experience, required
- 2+ years building and shipping production AI applications — LLM-powered apps, agentic workflows, RAG systems, or copilots — to real users, required
- Fluency with modern AI coding agents and developer tools (e.g., Claude Code, Cursor) and the surrounding DevOps stack — version control, CI/CD, testing, containerization, and cloud deployment.
- Deep experience working across both structured data (lakehouse, warehouse, transactional, and time series sources) and unstructured data (PDFs, documents, transcripts, semi structured sources) at scale. Hands on with document intelligence, OCR pipelines, LLM based extraction, and workflow automation that integrates these into end to end business processes.
- Strong coding fundamentals in Python and TypeScript or Java. Comfortable across the stack, from Spark transforms to React front ends.
- Experience working directly with business users to scope and ship software in regulated, high stakes environments. Financial services experience preferred but not required.
- Builder’s instinct under ambiguity. You start by shipping, measure progress in working software not slides, and can turn a vague business problem into a working prototype in a week.
- Customer obsession. You sit with users, reimagine workflows alongside them, and ship solutions that are functional in the real world rather than theoretical on a slide.
- Leverage mindset. You see every use case as an opportunity to make the next one faster. You build patterns, not snowflakes, and you invest in reusable building blocks that compound across the team’s work.
- Intellectual honesty about AI. You know what current models can and cannot do, you design around their limits, and you do not confuse demo magic with production reliability.
- Strong collaborator. You work well with business stakeholders and engineering peers, ask the right questions, communicate trade-offs clearly, and bring people along on the choices you make.
- Curious and self-directed. You look beyond assigned tasks to spot improvements, suggest alternatives, and contribute to how the team builds.
- Hunger to operate at the frontier. You want to build things that have never been built before, at a firm where the work matters.
Company Information
The Carlyle Group (NASDAQ: CG) is a global investment firm with $475 billion of assets under management, across 678 investment vehicles as of March 31, 2026. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,500 professionals operating in 28 offices in North America, Europe, the Middle East, Asia and Australia.
Carlyle’s purpose is to connect people, ideas, and capital to fuel growth for companies and performance for investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments – Global Private Equity, Global Credit and Carlyle AlpInvest – and has deep expertise across industries, markets, and geographies.
At Carlyle, we believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, "To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives." Reflecting this view, emphasis is placed on development, retention and inclusion through our internal processes and seven Employee Resource Groups (ERGs). We cultivate a culture where ideas are openly shared and challenged, connecting diverse expertise and perspectives to drive enduring value.