• Design and develop AI models, algorithms, and applications to solve mission‑driven problems. • Preprocess, analyze, and manage large datasets in collaboration with data and product teams. • Implement machine learning and deep learning frameworks. • Fine‑tune and optimize AI models for performance, scalability, and accuracy. • Integrate AI models into enterprise and cloud‑based production systems. • Document code, models, algorithms, and development processes. • Support testing, deployment, and ongoing operations of AI solutions. • Participate in SAFe Agile ceremonies and sprint planning. • Stay current with emerging AI technologies, tools, and best practices.

• Work closely with architects, engineers, and cross-functional stakeholders across Samsara to build AI-powered tools and maintain a robust AI infrastructure. • Rapid prototyping and iterative development of AI-based business applications and capabilities, with a focus on Generative AI. • Implement evaluation frameworks for AI applications that leverage foundational models. • Apply software engineering best practices. • Provide production support, monitoring, and troubleshooting issues.

• Design and implement solutions leveraging Generative AI and LLM-based systems • Develop and refine prompts for optimal model performance • Analyze and validate AI outputs to ensure accuracy, fairness, and reliability • Collaborate with cross-functional teams to integrate AI into business workflows • Optimize performance and cost trade-offs in LLM deployments • Contribute to enterprise-scale GenAI initiatives, including RAG architectures and document processing use cases

• Architect and implement the backend services that power multi-agent workflows. • Design scalable workflow engines and "human-in-the-loop" systems. • Create the integration layer between modern Python-based AI frameworks and Tenable’s robust JVM-based microservices architecture. • Implement verification layers, citations, and security guardrails to ensure agents operate deterministically and safely. • Build advanced Retrieval-Augmented Generation (RAG) pipelines and "Tool Use" capabilities. • Collaborate with researchers and product leads to define the roadmap for AI orchestration.