Principal Software Engineer - Llama Stack and Testing (EMEA)
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- Waterford
- Permanent
- Full-time
- Collaborate with Staff Engineers, Engineering, Product Management, and User Experience to define customer needs, use cases, and ensure product and testing fulfills those requirements
- Collaborate with Quality Engineers to develop and implement comprehensive unit, integration, and E2E tests to guarantee the reliability and performance in the upstream project, maintaining CI/CD workflows in GitHub, and ensuring downstream quality.
- Participate in AI-assisted code reviews, utilizing tools that provide real-time feedback, identify potential bugs, security vulnerabilities, and adherence to coding standards, contributing to a more thorough and efficient review process.
- Leverage AI-driven testing frameworks to automate test case generation, optimize test execution, identify potential edge cases, and enhance overall test coverage and reliability.
- Create and maintain clear, concise upstream technical documentation including API references and user guides and collaborating with our internal tech writers to create robust downstream documentation.
- 10 years of advanced Python and 5+ years Bash/Shell development experience
- The previous experience in testing, automation and quality engineering is mandatory.
- Advanced knowledge designing robust and scalable software used in highly scaled and performant Distributed Systems
- Experience with building agentic/RAG applications, MCP integrations, or developing with LLMs
- Advanced knowledge creating automation for GitHub, using GitHub Actions or related continuous integration tools.
- Advanced knowledge developing unit, functional, and end-to-end (E2E) test cases and automation, including frameworks such as PyTest
- Knowledge of Kubernetes/OpenShift and operational knowledge building/deploying containers.
- Experience developing, deploying or maintaining On-prem or Cloud Infrastructure
- Ability to quickly learn and use new tools and technologies.
- Experience with Security, Observability, Performance or Scale.
- Understanding of DevOps methodology, scrum, and/or Jira.
- Experience with AI and Machine Learning platforms, tools, and frameworks, such as LlamaStack, LangChain, PyTorch, LLaMA.cpp, vLLM, LangGraph, and Kubeflow.
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