Software Engineer - ADLC (All Genders)
Role details
Job location
Tech stack
Job description
The Software AI Engineer is responsible for contributing to the integration of AI capabilities across the software development lifecycle (SDLC) to improve engineering productivity, delivery quality, and automation within the PETS area of zooplus. This role focuses on contributing to the development of intelligent developer workflows using Model Context Protocol (MCP), context engineering, LLM orchestration, and AI-driven tooling., * Contribute to the design and implementation of AI-driven SDLC accelerators such as code generation, review automation, smart testing, and documentation support.
- Assist in the development of MCP-based extensions and context-aware tools to streamline developer workflows.
- Support the application of context engineering to improve LLM reasoning, accuracy, and relevance across engineering use cases.
- Contribute to building LLM-integrated CI/CD workflows for pull request analysis, test automation, and deployment support.
- Collaborate with engineering, platform, and product teams to support AI adoption opportunities.
Requirements
Do you have experience in Test automation?, Do you have a Master's degree?, * A tech-agnostic mindset with good programming experience in one or more of the following languages: Java, Python, JavaScript, or Kotlin.
- Experience with integrating LLMs into engineering or product workflows.
- Familiarity with RAG, embeddings, and vector databases.
- Experience with containerization and orchestration technologies like Docker and Kubernetes, and with Infrastructure as Code (Terraform).
- Experience with intelligent test automation and CI/CD pipelines.
Core Competencies
- MCP Engineering: Interest in building modular, context-aware AI tooling.
- Context Engineering: Understanding of how to structure inputs for reliable AI reasoning.
- AI-Augmented Architecture: Eagerness to learn about integrating AI into engineering systems.
- Product Thinking: Ability to identify high-value GenAI use cases.