AI Engineer Python

• Between 2 and 4 years of experience in Python development or DevOps automation, with at least 1 year implementing agentic workflows or structured generation with LLMs.
• Solid mastery of Python 3.11+ with strict typing, asynchronous programming (asyncio), and automated testing with pytest.
• Experience with agent frameworks (LangGraph, Microsoft Agent Framework, Pydantic AI or equivalents) and contract validation with Pydantic and JSON Schema.
• Deep knowledge of Azure Pipelines (YAML, templates, expressions, deployment jobs) and rendering engines such as Jinja2.
• Location in Madrid and the ability to work in multidisciplinary teams with a focus on security and code quality.

• Have experience with deployments on Kubernetes and management of manifests by environment.
• Handle schema validation tools (yamllint, dry-run) and documentation as code with Mermaid diagrams.
• Are passionate about learning, sharing ideas, and growing together with the team.

• Competitive salary range: 43,000 EUR - 45,000 EUR gross annual depending on experience.
• Location in Madrid with integration into high-visibility projects and real technological impact.
• Culture centered on technical excellence, autonomy, and continuous growth.
• Access to top-tier technical challenges at the intersection of GenAI, DevOps, and software architecture.

At Initium, we don't just develop technology: we create an environment where people can grow, add value, and leave their mark.

Apply now and let's talk.

Build the Next Generation of Agentic Automation at Initium

At Initium Software, we connect the best technical talent with the most challenging and innovative projects on the market. We are not a traditional consultancy; we are strategic partners who believe in real impact through technology. We are looking for an AI Engineer Python profile to lead the design and implementation of Generative AI agent chains aimed at transforming repositories and automating complex CI/CD workflows under a progressively agentic and deterministic SDLC model.

• Design, build, and maintain Generative AI agent chains to transform repository contexts into compliant and validated Pull Requests.
• Implement decoupled architectures where agentic logic is isolated from the framework and the LLM provider through robust interfaces.
• Guarantee the deterministic rendering of YAML templates (Azure Pipelines, Kubernetes) by combining template engines with structured generation.
• Index and retrieve corporate catalogs using advanced RAG techniques and context minimization.
• Ensure compliance with technical governance standards, strict change review, and the principle of least privilege.

• Achieving monthly project efficiency goals.
• Aligning with and effectively executing the strategic plan.