Staff Software Engineer (Agentic Systems) – AI for Software Delivery

DescriptionJob Title: Staff Software Engineer (Agentic Systems) – AI for Software Delivery 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 embedding AI across the entire software development lifecycle to reduce the time it takes to understand, triage, and resolve problems - from planning and code, through CI/CD, to production systems. As a Staff Engineer, you will lead the design and evolution of agentic systems that operate across the SDLC. These systems ingest signals from multiple sources - code, pull requests, tests, pipelines, incidents, and documentation - and reason over them to provide high-confidence insights and, over time, take safe, constrained actions. This is not just about adding AI to existing workflows. It’s about defining how intelligent systems participate in software delivery, where context is fragmented, systems are interdependent, and correctness matters. You will work across team and product boundaries to:

• Define architectures for cross-SDLC agentic workflows
• Establish patterns for reasoning, context synthesis, and tool orchestration
• Connect signals across traditionally siloed systems (e.g. code ? CI ? incidents ? docs)
• Drive the evolution from advisory systems to controlled, auditable automation
• Ensure these systems are reliable, observable, and safe in production environments

This role requires both deep technical execution and strong technical leadership, including shaping direction, influencing multiple teams, and raising the bar for how AI systems are built and operated. What You’ll Do

• Lead the design of AI-driven systems that triage, explain, and eventually remediate CI/CD failures across products
• Define and evolve agent architectures, including reasoning strategies, tool orchestration, and context management
• Drive cross-team technical initiatives, aligning platform, product, and infrastructure components
• Translate ambiguous problem spaces into well-defined systems and execution plans
• Establish engineering standards and patterns for:

• agent reliability and correctness
• evaluation and benchmarking
• observability and tracing
• safety and guardrails

• Improve system performance across:

• reasoning quality
• tool-call accuracy
• latency and cost efficiency

• Mentor engineers and raise the technical bar across the team
• Partner with product and leadership to shape roadmap and technical strategy

Contribute to build vs buy decisions, platform direction, and long-term architecture RequiredWhat We’re Looking For

• 8+ years of software engineering experience, including experience operating at a strong senior or staff level
• Proven experience designing and delivering complex, distributed systems in production
• Strong programming skills in Python, Go, or TypeScript
• Deep experience with cloud-native architectures (AWS or GCP)
• Hands-on experience building LLM-based or AI-assisted systems, including:

• prompt and context design
• tool integration and orchestration
• evaluation frameworks and metrics
• guardrails and safety mechanisms

• Experience defining and operating systems with:

• high reliability and availability
• strong observability (metrics, tracing, logging)
• clear failure modes and recovery strategies

• Demonstrated ability to:

• lead technical initiatives across teams
• operate effectively in ambiguous problem spaces
• balance speed of iteration with production quality

Preferred

• Experience building agentic systems or multi-step reasoning workflows
• Familiarity with CI/CD ecosystems (Jenkins, GitHub Actions, Argo, etc.)
• Experience with LLM evaluation frameworks, tracing tools, or RAG systems
• Understanding of trade-offs between autonomy, safety, and control in AI systems
• Experience influencing architecture or strategy at a product or platform level

What Success Looks Like In your first 3–6 months, you will:

• Deliver AI-assisted workflows that materially reduce time-to-triage for software failures
• Establish baseline evaluation frameworks for reasoning quality and system reliability
• Lead the design of core agent architecture used across multiple workflows
• Influence the roadmap toward safe, incremental automation

In 6–12 months:

• Drive adoption of agentic systems across multiple product areas
• Improve agent accuracy, reliability, and trust to production-grade levels
• Establish standards and best practices used by multiple teams
• Be a go-to technical leader for AI systems within the organization

Why This Role Many AI roles focus on chat interfaces or generic copilots. This role is different. You’ll work on high-signal, structured problems inside real engineering systems, where:

• context is fragmented and dynamic
• correctness directly impacts production systems
• and trust must be earned before automation is possible

You won’t just build features. You’ll help define how AI operates inside mission-critical software delivery systems. Compensation & Benefits Base Pay Range: AUD 170,000 – AUD 190,000 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.