> Markdown version of [/jobs/ext/3661586-sr-software-engineer-ii-devex](https://www.wearedevelopers.com/jobs/ext/3661586-sr-software-engineer-ii-devex). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Sr. Software Engineer II, DevEx

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $154,200.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Continuous Integration, Systems Development Life Cycle, Software Engineering, Technical Debt, Information Technology, Automation Anywhere
- **Published:** October 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pq00qamdnw

## About the Role

* 8+ years of experience in software engineering
 * Bachelor's degree in Computer Science, Engineering, or equivalent experience
 * 3+ years of experience in developer experience, CI/CD, or platform engineering
 * Experience building AI workflows and orchestration systems
 * Proven track record architecting CI/CD systems and automated response workflows
 * Familiarity with cloud platforms such as AWS and GCP
 * Strong leadership and direction-setting skills

## Description

This role will focus on advancing developer experience and engineering productivity by improving CI/CD systems, deployment safeguards, and automated workflows. The engineer will partner closely with platform and application teams to reduce friction in the software delivery lifecycle and help bring AI-enabled automation into production in a scalable, reliable way. The work will have direct impact on pull-request throughput, operational resilience, and the effectiveness of the broader engineering organization., * Scale internal CI/CD systems to support increased pull-request throughput

 * Reduce technical debt using AI workflows
 * Design deployment safeguards to protect production at scale
 * Build observability and feedback systems for AI-driven automation
 * Serve as a thought leader on AI to enhance engineering productivity
 * Redefine the outer loop of the SDLC with AI-native workflows
 * Experiment with new AI capabilities and convert successful approaches into production-ready systems