Ticketmaster is looking to solve the problem of tech debt reduction, enable teams with automation and AI tools, and raise the bar for operational excellence in their Core Concerts division.
Requirements
- 5+ years of hands-on software engineering experience; systems or backend engineering preferred.
- Hands-on experience with AI developer tools (GitHub Copilot, Cursor, etc), LLM-backed scripting, automation frameworks, and agentic AI systems capable of planning, tool use, and autonomous task execution in engineering workflows.
- Strong knowledge of at least one scripting language (Python, Bash) and exposure to infrastructure tooling (e.g., Terraform, CI/CD pipelines).
- Experience with automated VM deployments (VMware) and automated configuration management (Ansible).
- Experience in SRE, DevOps, or platform engineering environments—or the curiosity to quickly ramp up in that domain.
- Excellent communication and collaboration skills; you enjoy being a multiplier.
- Experience containerizing software and tools (Docker, Podman) and deploying them in orchestrated environments.
Responsibilities
- Write high-quality, maintainable code to accelerate platform automation and reduce tech debt across Core Concerts systems.
- Use scripting (Python, Bash, etc.) and infrastructure-as-code (Terraform, Ansible, etc.) to simplify operational workflows.
- Lead technical deep-dives to identify automation opportunities and tackle long-standing inefficiencies.
- Drive adoption of AI developer tools like GitHub Copilot, Ollama, Amazon Q, etc. across the team.
- Champion the use of agentic AI systems that plan, reason, and act—building frameworks that enable autonomous task execution and tool chaining.
- Help define and evolve our internal patterns for LLM-backed development and AI-augmented refactoring workflows.
- Collaborate closely with reliability and platform engineers to deliver automation that sticks—measurable impact over buzzwords.
Other
- Work well across teams – You communicate clearly, share context, and collaborate effectively with engineers across disciplines to get things done.
- Take ownership – You don’t wait for permission to fix what’s broken. You identify problems, propose solutions, and follow through.
- Think in systems – You design for scale, reliability, and maintainability. You simplify where possible and automate where it counts.
- Move with intent – You prioritize impact over perfection. You ship improvements iteratively and measure results.
- Push tooling forward – You adopt and advocate for tools that make engineering faster and smarter—especially AI-driven ones.
