Job Title: Senior Software Engineer (Agentic) – AI & Workflow Automation
Job Type: Full-time
Location: Remote - Australia

About CloudBees

CloudBees helps enterprises deliver secure, compliant software at scale. We sit at the center of the software delivery lifecycle, from Jenkins-based CI to modern cloud-native DevSecOps platforms.

Our focus is simple: make software delivery faster, safer, and more reliable for large engineering organizations.

About the Role

We’re building AI capabilities directly into the software delivery lifecycle to reduce the time it takes to understand, triage, and resolve issues in CI/CD systems.

This role is focused on designing and building AI-assisted workflows that help engineers diagnose and fix problems in complex delivery pipelines. Today, these systems operate in a read-only, advisory capacity. Over time, we will evolve toward safe, constrained automation.

You will work on:

• Understanding CI/CD signals (logs, test failures, pipeline state)
• Building agents that can reason over this data and provide actionable insights
• Designing systems that are reliable, observable, and safe to operate in production environments

This is a hands-on role for someone who can move from prototype to production, and who is comfortable working in an evolving problem space.

What You’ll Do

• Design and build AI-driven workflows to triage and explain CI/CD failures
• Develop agents that interact with APIs, logs, and developer tools to gather and synthesize context
• Translate early prototypes into production-ready services and pipelines
• Improve agent reliability across:

• reasoning quality
• tool usage accuracy
• latency and performance

• Define and implement guardrails and safety boundaries for agent behavior
• Work closely with product and platform teams to integrate these capabilities into CloudBees products
• Instrument systems with metrics and tracing to evaluate and improve agent performance

What We’re Looking For
Required

• 5+ years of software engineering experience
• Strong programming skills in Python, Golang, or TypeScript
• Experience building backend systems or services in cloud environments (AWS or GCP)
• Hands-on experience working with LLM-based systems, including:

• prompt design
• tool integration
• evaluation of outputs
• guard-rails

• Experience designing and operating reliable production systems (observability, scaling, failure handling)
• Ability to move between rapid prototyping and production implementation

Preferred

Experience building or operating AI agents or multi-step workflows
Familiarity with CI/CD systems (e.g. Jenkins, GitHub Actions, Argo)
Experience with LLM evaluation, tracing, or debugging tools

• Understanding of trade-offs between autonomy, safety, and control in AI systems
• Experience working in fast-moving or early-stage product environments

What Success Looks Like

In your first 3–6 months, you will:

• Ship AI-assisted workflows that reduce time to triage CI failures
• Improve the accuracy and usefulness of agent-generated insights
• Help define the path from advisory systems to safe, automated actions
• Establish metrics to measure reasoning quality and system reliability

Compensation & Benefits

Base Pay Range: AUD 135,000 – AUD 165,000 annually
Actual compensation will vary based on experience and location.

In addition to base salary:

• Stock options
• Variable bonus
• Flexible remote work
• Health and wellness benefits (region-specific)
• Retirement plans (region-specific)

Equal Opportunity

CloudBees is an Equal Opportunity Employer. We are committed to building an inclusive environment for all employees.

Why This Role

Most AI roles focus on chat interfaces or generic copilots. This role is different.

You will work on high-signal, structured problems inside real engineering systems, where:

• context is messy
• correctness matters
• and partial answers are not enough

If you’re interested in building AI systems that engineers actually rely on in production, this is that opportunity.