About the position
CloudBees is the leading software delivery platform for enterprise DevOps teams. As a startup in the developer operations space, we empower organizations to build, test, and release software with speed, security, and intelligence. Now, we’re evolving our platform with agentic AI technologies that help developers work smarter, not harder. CloudBees is looking for a creative and technically sharp Software Engineer to help architect and prototype AI/LLM-driven workflows that augment developer productivity. This is a hands-on engineering role focused on building agentic flows using tools like Goose, Unify MCP, AWS Q, and Gemini. If you thrive in ambiguity, love to prototype rapidly, and have a track record of shipping innovative ML/AI-powered features in startup environments, we want to talk. As a member of the AI Foundations founding team, this is a high-impact role that sits at the intersection of artificial intelligence and software delivery – ideal for someone passionate about pushing the boundaries of developer productivity and intelligent automation.
Responsibilities
- Design, prototype, and test agentic workflows using platforms like Goose, Unify MCP, AWS Q, and Google Gemini.
- Build and iterate on AI-powered agents that can autonomously interact with systems, APIs, and developer tools.
- Translate product concepts into working demos and scalable pipeline implementations.
- Collaborate cross-functionally with product managers, ML engineers, and DevOps teams to refine user workflows.
- Optimize agent behavior for reasoning, autonomy, reliability, and safety.
- Contribute to ML pipeline development for deploying and monitoring agentic flows in production environments.
- Document architectures and share learnings across the engineering org.
Requirements
- 3+ years of experience with agentic systems and LLM.
- 5+ years of hands-on experience in AI/ML engineering, LLM Ops.
- Proven knowledge & experience developing agentic flows with frameworks like Langchain, CrewAI, Agno, or custom.
- Familiarity with prototyping and testing in environments with MCP enabled tools like Claude Desktop/Goose, AWS Q, and Gemini.
- Experience designing and maintaining pipelines for ML models, workflows, or LLM agents.
- Strong programming skills in Python and TypeScript.
- Comfortable working in cloud-native environments (AWS/GCP) and with DevOps pipelines (e.g., GitHub Actions, Argo).
- Startup experience or demonstrated ability to build fast, iterate quickly, and wear multiple hats.
Nice-to-haves
- Experience integrating agentic workflows into SaaS developer platforms.
- Familiarity with orchestration, memory management, and context-aware agents.
- Understanding of prompt engineering, tool augmentation, and LLM fine-tuning.
- Knowledge of system observability and debugging tools for agents.
Benefits
- Build at the frontier of agentic AI + DevOps, solving real developer pain points.
- Work with a passionate, globally distributed team in a flexible startup culture.
- Have an outsized impact on product direction and innovation.
- Competitive compensation, equity, and full remote benefits.
