Staff Software Engineer (Agentic AI Platform)

About this role

• Join Cloudera’s Machine Learning Platform team as a Staff Software Engineer. You will be a core technical leader responsible for designing, building, and delivering our next-generation AI and MLOps platform
• You will design, build, and deliver an enterprise-grade platform enabling enterprises to create, deploy, and orchestrate agentic applications and multi-agent platforms using foundation models with enterprise data at scale in a hybrid cloud environment
• As a Staff-level engineer, you will drive technical architecture, advocate for engineering best practices, and collaborate closely with cross-functional teams (Product, Design, Frontend, and Field Engineering) to enhance developer velocity and platform agility
• Architect and Build: Design, code, and implement elegant, scalable, enterprise-quality platform and application services / SDKs that support autonomous agents, multi-agent collaboration, and advanced tool-use capabilities
• Implement Agentic Evaluation & Observability: Build automated evaluation pipelines and trajectory tracking to continuously bench, audit, and evaluate agent reasoning loops, tool-calling accuracy, and guardrail compliance
• Architect Memory Management Systems: Develop and optimize robust stateful memory architectures for enterprise agents, handling short-term context window strategies, long-term semantic/episodic memory persistence, and secure cross-session state management
• Enable RAG use cases: Implement AI application services powered by machine learning models, enabling scalable Retrieval-Augmented Generation (RAG) and semantic search
• Lead by Example: Advocate for and establish engineering best practices, coding standards, and rigorous system design methodologies
• Enhance Platform Velocity: Work to enhance developer velocity, framework abstraction, and team agility across the AI platform ecosystem
• Collaborate Cross-Functionally: Build strong relationships and collaborate with platform and UI engineers, data scientists, qual...