Senior Platform Support Engineer

🏢 Autodesk · all Autodesk jobs
📍 Ireland
💰 EUR 71,000 - 104,500 / annual
📅 Posted 2026-08-19 · via Himalayas
🏷 Platform-Engineering,DevOps,Site-Reliability-Engineering,Developer-Relations,Cloud-Engineer,Platform-Support-Engineer,Senior-Support-Engineer,Senior-Platform-Engineer,Senior-Technical-Support-Engineer,Senior-DevOps-Platform-Engineer,Support-Engineer
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Job Requisition ID #

26WD95293 Job Description for Senior Platform Engineer

Position Overview

We are seeking a Senior Platform Developer to join the Platform Services and Emerging Technology organization within the Developer Enablement (DevRel) group.

Our mission is to enable developers with the tools, platforms, and support needed to build, test, and deploy high-quality applications at scale using Autodesk developer platforms (e.g., CloudOS, Beacon). The DevRel team drives knowledge sharing, collaboration, and developer empowerment across internal and external engineering teams.

In this role, you will act as a senior-level technical leader for developer enablement and onboarding platforms across Americas, Canada, and EMEA . You will design and evolve systems that improve developer productivity, onboarding velocity, and platform reliability.

This role requires strong hands-on expertise in cloud platform engineering, AI/ML systems, and agentic AI workflows , particularly leveraging LLM-based automation to improve onboarding, troubleshooting, and developer self-service experiences .

You will design and operate cloud-native applications, CI/CD systems, and Infrastructure-as-Code automation using technologies such as Terraform, Helm, and Kubernetes.

You will also leverage AI/ML and agentic AI systems to introduce intelligent automation across developer onboarding, troubleshooting, and platform self-service workflows , enabling a next-generation developer enablement experience.

You will report to a Senior Engineering Manager.

Responsibilities

- Own and drive the architecture and evolution of developer onboarding and enablement platforms

- Standardize and improve service deployment processes across application teams

- Accelerate onboarding and deployment timelines through scalable platform automation

- Design and implement cloud-native automation to reduce manual effort across onboarding workflows

- Build and support developer enablement tooling and internal platform services

- Provide hands-on technical guidance and support for developers using internal platforms

- Troubleshoot complex platform and integration issues across distributed systems

- Collaborate with application and platform teams to ensure evolving developer needs are met

- Design and implement AI/ML and agentic AI solutions to automate onboarding, enhance troubleshooting, and improve developer self-service capabilities

- Apply AI-driven automation to improve platform efficiency, reliability, and developer experience at scale

- Define and contribute to technical roadmap planning for platform modernization and automation initiatives

- Create and maintain high-quality technical documentation, runbooks, and enablement materials

- Stay current with emerging technologies in cloud platforms, AI/ML, and agentic AI systems

Minimum Qualifications

- Bachelor’s or Master’s degree in Computer Science or related field

- 8+ years of experience building scalable cloud-native applications using Python, Node.js, or similar frameworks

- 8+ years of experience in cloud platforms (AWS preferred)

- 8+ years of experience designing and implementing CI/CD pipelines and SDLC automation (Jenkins, CloudBees, Spinnaker, etc.)

- 8+ years of experience with Infrastructure-as-Code and platform automation tools (Terraform, Helm, Ansible, etc.)

- Experience with containerized and distributed systems using Docker and Kubernetes

- Strong understanding of cloud networking, observability, and distributed system design

- Strong troubleshooting, debugging, and incident resolution skills

- Experience creating operational documentation (runbooks, engineering guides, system design docs)

- Strong collaboration and communication skills across engineering teams

- Hands-on experience building and deploying production AI/ML systems

- Experience with agentic AI systems or LLM-based automation workflows (tool use, orchestration, autonomous agents)

- Proven ability to operate

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