CloudBees is looking to integrate agentic intelligence into its platform to supercharge developer workflows and augment developer productivity. The company needs a data scientist to drive insights and tell the story behind the metrics related to these AI/LLM-driven workflows.
Requirements
- 3+ years of experience in agentic systems, 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, TypeScript,
- Comfortable working in cloud-native environments (AWS/GCP) and with DevOps pipelines (e.g., GitHub Actions, Argo).
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.
- 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.
- Collaborate cross-functionally with product managers, ML engineers, and DevOps teams to refine user workflows.
Other
- Startup experience or demonstrated ability to build fast, iterate quickly, and wear multiple hats.
- 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.
