Engineer, AI & Process Automation

The Carlyle Group•Washington, DC

48d•$160,000 - $180,000•Hybrid

About The Position

The Engineer, AI & Process Automation sits within Carlyle’s Corporate Services Technology organization, reporting to the Lead Engineer, AI & Process Automation, and contributes hands on to the team’s mission of delivering AI and automation solutions across business domains including Finance, Tax, Human Capital, Legal & Compliance, and Marketing & Communications. Corporate Services is where AI can compound the firm’s operating leverage fastest: high-volume document and data workflows, deep institutional knowledge, and clear measures of throughput and quality. We are building Carlyle’s next generation of AI native products against that opportunity, and we are investing aggressively in the talent, tooling, and platforms required to win. This is a builder’s role on the team driving Carlyle’s AI and process automation work for Corporate Services: a hands on engineer who embeds with the business, owns delivery on the products they build, and operates with full accountability for the outcomes they ship. You will embed directly with Carlyle’s Corporate Services functions Finance, Tax, Human Capital, Legal & Compliance, Marketing & Communications, and the other enterprise teams that run the firm working with your manager and team to take the highest leverage AI opportunities from idea to production, and translating ambiguous business problems into working software in weeks, not quarters. You will build custom AI solutions using modern coding agents and developer tools Claude Code, Cursor, and the surrounding DevOps stack to deliver applications, agentic workflows, and copilots tailored to how Corporate Services actually works. Carlyle takes a best of breed approach to AI, and you will work within that approach reaching for the right models, frameworks, and tools for each problem rather than defaulting to a single vendor. You will contribute to engineering quality across the team sharing patterns, reviewing each other’s code, and helping reusable building blocks compound across the work the team ships.

Requirements

Bachelor’s degree, required
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.

Nice To Haves

Concentration in computer science, software engineering, mathematics, physics, data science, or a related technical field, preferred
Master’s degree, preferred
Financial services experience preferred but not required.

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.