Engineer, AI & Process Automation

Position Summary 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 and 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. What Success Looks Like In the first 12 months, you will have shipped multiple production AI products embedded in real Corporate Services workflows, contributed reusable patterns and building blocks that accelerate the team’s subsequent work, and earned a reputation as a trusted technical partner to the business stakeholders you serve. Your work will be visible at senior levels of the firm. In‑office requirement: 4 days a week. Responsibilities Solution Delivery (≈75%) 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. Engineering Craft & Reusability (≈25%) 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 Education & Certifications Concentration in computer science, software engineering, mathematics, physics, data science, or a related technical field, preferred Professional Experience 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. Compensation & Benefits The compensation range for this role is specific to Washington, DC, and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications. The anticipated base salary range for this role is $160,000 to $180,000. In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance. #J-18808-Ljbffr Carlyle