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# Staff Software Engineer

- **Company:** RB Global Inc.
- **Location:** Westchester, IL, United States
- **Experience:** Expert
- **Salary:** $123,950 - $154,880
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Audit Trail, Continuous Integration, Python (Programming Language), Software Engineering, Datadog, Data Logging, GitHub Copilot, Agentic-AI, Kubernetes, Model Context Protocol, Golang
- **Published:** November 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bcc48f9dbb4ddb7c

## About the Role

* Significant professional software engineering experience at a staff level of scope and judgment (8+ years of professional experience), including time spent setting technical direction collaboratively rather than solo.
 * Experience contributing to internal developer platforms, "paved road" tooling, or developer-enablement work, since this team exists to make other engineers more effective.
 * Deep, hands-on experience setting up and operating CI/CD pipelines, including defining and enforcing quality gates as code.
 * Deep understanding of Kubernetes or comparable container orchestration, and comfort owning services from build through production operation.
 * Strong, practical knowledge of observability, such as structured logging, tracing, and metrics/dashboards (e.g., Datadog, OpenTelemetry, or similar), and using it to answer "is this actually working?"
 * Enterprise-level experience with Python, Java, Go or similar high-level languages; we care more about your ability to reason across a stack and pick up what's needed than mastery of any one language.
 * A track record of building things that other engineers adopt voluntarily, because you think about rollout, documentation, and the path of least resistance, not just whether the code works.
 * Curiosity and a genuine desire to learn: this space is moving fast, the right answers aren't settled yet, and the best candidates will enjoy figuring them out rather than expecting a playbook.
 * Strong communication skills, with the ability to explain technical trade-offs clearly to teammates, other engineering teams, and stakeholders who weren't in the room when the decision was made.
 * Comfort translating ambiguous or evolving problems into a concrete technical approach, since much of this team's early work won't have a settled playbook to follow.

Nice To Have

 * Experience using AI-assisted development tools (e.g., GitHub Copilot, agentic coding tools), and even better, experience building platforms, tooling, or guardrails around them.
 * Experience building AI tooling, personal or professional, and a natural enjoyment of experimenting with new approaches.
 * Familiarity with MCP (Model Context Protocol) or similar tool-access and governance patterns.

## Description

* Help design and build secure, governed ways for agents to reach internal tools and data, with the scoping, credentials, and audit trails that make that access trustworthy.
 * Build and run the containerized environments agents work in, where things like isolation, reproducibility, and model/cost choices are actually controlled.
 * Take the team's engineering standards and conventions and turn them into something tools and agents can actually consume and follow, not just documentation that drifts out of date.
 * Establish the baselines and metrics the team doesn't have yet, so claims about speed, quality, and cost are backed by numbers.
 * Partner with CI/CD, security, and platform teams to plug agent workflows into tools the company already uses, rather than reinventing them.
 * Review and harden what the team ships with the same rigor you'd apply to any system other engineers depend on: tests, documentation, and a clear plan for who supports it.
 * Work with teammates to decide what the team takes on, and when to adopt an existing tool versus build something new.
 * Own the design and architecture of the solutions you build, and work across multiple initiatives and team boundaries as the team's scope grows.
 * Partner with the team's technical product owner and stakeholders across the company to shape direction, priorities, and the stories that turn ideas into delivered work.
 * Work closely with the other engineers on the team to reason through ambiguous problems together, rather than any one person directing the work.