AI Platform Engineer

Carlyle is hiring an AI Platform Engineer to join our Enterprise Technology team. In this role, you will partner with engineering teams, product owners, and other business stakeholders to design, build, and maintain the AI enabled developer platforms used across our global technology organization.

As an AI 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 spend your time 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.

You will be instrumental across the full lifecycle of our AI developer platforms, from prototyping new agentic workflows and evaluating emerging tooling to product ionizing the infrastructure that runs them. You will build internal frameworks, skills and tool registries, MCP integrations, and supporting platforms that allow engineers to safely leverage AI across every stage of software delivery, from issue triage and code generation through review, testing, and deployment.

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  will also promote these practices across the firm, partnering with engineering teams to drive adoption and measurable productivity gains.

• AI-Enabled Development:
  Hands on experience integrating AI coding assistants and agentic tooling into engineering workflows, including tools such as Claude Code, Cursor, MCP-based integrations, Coder, and Amazon Bedrock Agent Core. Familiarity with the surrounding scaffolding (skills, agents, registries, hooks, and guardrails) that makes these tools usable in an enterprise environment.
• Platform Engineering Fluency:
  Demonstrated experience building and operating internal developer platforms (IDPs) at scale, including paved roads, self-service interfaces, and golden path templates. You think of the platform as a product and treat developers as your customers.
• 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 the majority of working hours writing 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.
• Design, build, and operate AI enabled developer platforms serving a development community of over 500 engineers across the technology organization.
• Integrate AI coding assistants and agent runtimes (Claude Code, Cursor, Amazon Bedrock Agent Core, and similar) into developer workflows, including the harnesses, hooks, and reference patterns required to use them effectively in an enterprise setting.
• 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.
• Implement paved-road developer experiences across source control, CI/CD, environments, observability, security, and release management, with AI capabilities integrated where they add value.
• 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.

• 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…