Senior Platform Support Engineer

Autodesk Autodesk · Enterprise · Dublin, Ireland

Senior Platform Support Engineer role focused on enabling internal developers by providing technical support for platforms, CI/CD systems, and developer tooling. The role involves troubleshooting complex issues, driving root cause analysis, and improving developer experience. A key aspect is leveraging and applying AI/LLM-based workflows and intelligent automation pragmatically to solve recurring problems, enhance self-service, and improve overall engineering effectiveness within the developer ecosystem.

What you'd actually do

  1. Provide advanced, hands-on technical support for internal developers using shared platforms, CI/CD systems, and developer tooling
  2. Triage and resolve complex, non-trivial issues across CI/CD pipelines (Jenkins, CloudBees, GitHub Actions), deployment platforms (CloudOS, Spinnaker, Kubernetes), GitHub Enterprise, Artifactory, API platforms (Apigee / APIM), observability tools (Splunk), and AWS services
  3. Act as a senior escalation point for ambiguous or cross-platform problems that require deep systems understanding and structured troubleshooting
  4. Perform root cause analysis for recurring platform and pipeline issues, and work with partner platform teams to drive durable fixes and improvements
  5. Partner closely with internal product, platform, and infrastructure teams to unblock delivery and improve the developer experience

Skills

Required

  • platform engineering
  • SRE
  • DevOps
  • advanced technical support
  • AI/LLM-based workflows
  • autonomous or agentic systems
  • CI/CD systems
  • Kubernetes
  • AWS cloud infrastructure
  • observability concepts
  • observability tools
  • Python
  • Shell
  • Bash
  • Groovy

Nice to have

  • supporting internal developer platforms at scale
  • Spinnaker
  • Apigee
  • Artifactory
  • enterprise platforms
  • productionizing AI/LLM-powered applications
  • intelligent automations
  • agentic workflows
  • AI-enabled developer productivity solutions
  • platform capabilities
  • internal engineering tools
  • DevRel
  • platform enablement
  • internal support engineering
  • automation using APIs
  • bots
  • AI-assisted tooling
  • globally distributed teams

What the JD emphasized

  • 8+ years of experience
  • Experience designing, integrating, or operating AI/LLM-based workflows, including autonomous or agentic systems that interact with tools, APIs, or enterprise data sources
  • Strong hands-on experience with CI/CD systems (Jenkins/CloudBees, Spinnaker/Harness, Artifactory, GitHub, or similar)
  • Practical experience supporting Kubernetes-based platforms and cloud deployments
  • Solid understanding of AWS cloud infrastructure
  • Solid understanding of observability concepts, including logs, metrics, and traces, and experience using observability tools (Splunk, Dynatrace, Catchpoint, BigPanda, etc…) to diagnose platform and pipeline issues

Other signals

  • applying AI pragmatically to improve how developers interact with platforms
  • identifying opportunities where AI can enhance self-service, workflow efficiency, and engineering effectiveness
  • Experience designing, integrating, or operating AI/LLM-based workflows, including autonomous or agentic systems that interact with tools, APIs, or enterprise data sources
  • Ability to evaluate when AI-driven approaches are appropriate and apply them pragmatically to real engineering problems
  • Experience designing and productionizing AI/LLM-powered applications, intelligent automations, or agentic workflows in enterprise environments
  • Experience building AI-enabled developer productivity solutions, platform capabilities, or internal engineering tools used at team or organizational scale
  • Exposure to automation using APIs, bots, or AI-assisted tooling