DevEx Platform Engineer

Carlyle is hiring a DevEx Platform Engineer to join our Enterprise Technology team. In this role, you will partner with engineering teams, product owners, and other business stakeholders to build, operate, maintain, and troubleshoot the AI-enabled developer platforms used across our global technology organization. As an DevEx Platform Engineer, you will play a pivotal role in enabling modern AI-driven development across our engineering organization, supporting a development community of over 500 users. Your work will directly shape how Carlyle’s engineers design, build, test, and ship software in an AI-native way. You will split your time between building and running these platforms—writing code, building agentic frameworks, integrating AI coding assistants into the SDLC, and creating the platforms, registries, and abstractions that make AI-driven development safe, repeatable, and scalable inside the firm, while owning their reliability and performance in production. You will be instrumental across the full lifecycle of these platforms, from evaluating emerging tooling and prototyping new agentic workflows to operating them as production services. You will define and maintain the SLOs, observability, and response practices that keep the platforms dependable, troubleshoot issues as they surface, and continuously look for ways to reduce operational toil so engineers can rely on our platforms the same way they rely on any other production system. You will work with application engineering, cloud operations, security, and architecture teams to identify friction in the developer experience and deliver paved-road platforms that make AI-driven practices the default way of working at Carlyle. You will also promote these practices across the firm, partnering with engineering teams to drive adoption and measurable productivity gains. The ideal candidate has the following skills and competencies: Operational Reliability: Treats running the platform as a first‑class responsibility. Experience defining SLOs and SLIs, instrumenting services with metrics, logging, and tracing, responding to incidents, and conducting blameless post‑mortems. Reduces operational toil through automation. Observability: Hands‑on experience with modern observability platforms (Datadog, Grafana, OpenTelemetry, or similar). Builds dashboards, alerts, and traces that surface the right signals at the right time, and partners with engineering teams to instrument their services for production readiness. Communication: Able to articulate the value of AI and platform investments to a range of stakeholders, and to build credibility with both technical and non-technical colleagues. Hands‑On Engineering: Spends a significant portion of working hours writing and automating code. Comfortable with production code, building integrations, debugging pipelines, and shipping features end‑to‑end across distributed systems. Adaptability: Comfortable with ambiguity and committed to ongoing learning as the AI tooling landscape evolves. Looks for practical ways to improve the developer experience. Responsibilities Operate and monitor AI‑enabled developer platforms in production: define SLOs and SLIs, build dashboards and alerting, and ensure the reliability, performance, and availability of the services engineering teams depend on every day. Drive troubleshooting and remediation of production issues when platform services degrade, and run blameless post‑mortems that turn incidents into lasting reliability improvements. Automate operational tasks to reduce toil, and continuously tune capacity, cost, and performance as platform adoption grows. Design, build, and operate AI‑enabled developer platforms serving a development community of over 500 engineers across the technology organization. Build and maintain agentic frameworks, skills and tool registries, MCP gateways, and the supporting infrastructure that allows engineering teams to safely and effectively use AI across the software delivery lifecycle. Develop self‑service cloud development environments and internal developer portal capabilities (using platforms such as Coder) that let application teams provision, configure, and operate their environments with minimal central involvement. Prototype and evaluate new AI development tools, agent runtimes, and orchestration patterns, and incorporate the most useful capabilities into the platform. Partner directly with engineering teams across the firm to drive adoption of AI‑enabled development practices and translate user feedback into platform improvements. Collaborate with security, networking, cloud operations, and architecture teams to ensure platform capabilities are secure, compliant, and well‑integrated with existing infrastructure, and contribute to internal documentation and reference implementations that help engineers get the most out of AI‑driven development. Qualifications Education & Certificates Bachelor’s Degree required Concentration in Computer Science, Software Engineering, Information Technology, or similar discipline, strongly preferred AWS Certified Solutions Architect, AWS Certified Developer, or similar cloud certifications preferred Industry‑standard certifications in platform engineering, Kubernetes, or AI/ML preferred Professional Experience 5+ years of relevant software or platform engineering experience, required. Hands‑on experience integrating AI platforms and tooling into enterprise engineering workflows, including agent runtimes, AI coding assistants, MCP‑based integrations, and the supporting infrastructure required to operate them safely at scale. Practical experience implementing and managing AI development tools such as: Claude Code, Cursor, MCP servers, Coder. Hands‑on experience operating production services using SRE practices, including defining and measuring SLOs/SLIs, managing error budgets, and reducing operational toil through automation. Proficiency with observability and monitoring tooling (such as ELK, Datadog, OpenTelemetry, or CloudWatch) to instrument, alert on, and troubleshoot distributed systems. Experience troubleshooting and remediating production issues, including triage, mitigation, and blameless post‑mortems. Strong hands‑on experience with AWS, including the services that underpin modern developer platforms (EKS, ECS, Lambda, API Gateway, IAM, VPC, S3, and similar). Strong proficiency with GitHub Enterprise, including GitHub Actions, reusable workflows, and platform‑level patterns such as IssueOps and workflow orchestration. Strong proficiency with infrastructure as code (Terraform) and modern CI/CD practices for both application and platform delivery. Strong proficiency in at least one general‑purpose programming language (Python, TypeScript, Go, or similar) and comfort writing production code. Strong understanding of cloud security principles, identity and access management, and secure‑by‑default platform patterns. Commitment to ongoing learning as AI and developer tooling continue to evolve. Strong problem‑solving skills, with a track record of troubleshooting distributed systems and developer tooling issues. Strong interpersonal and communication skills, with the ability to explain complex topics and present to both technical and non‑technical audiences. Proven collaboration skills across multiple technology and project teams to deliver effective solutions. Ability to communicate clearly in presentations and written documentation. Ability to prioritize and deliver across competing demands. 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. Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle. #J-18808-Ljbffr Carlyle