Production AI Agent Engineer for Scalable LLM Systems

Mondia; Madrid; Híbrido; EUR 65.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Company bonus

Private health insurance

Creative office

International team

Descripción de la vacante

Mondia in Madrid is seeking a software engineer to build production AI agents and related tooling. You will own the agent logic, data layers, and pipelines, delivering reliable, scalable systems for internal use across engineering teams.

You will write clean Python, work on RAG pipelines, Postgres schemas, and integration with Git, CI/CD, and internal services. This role demands hands-on coding, debugging, and collaboration in a high-ownership environment.

Formación

• 4+ years of professional Python software engineering.
• 1+ year building LLM/agentic systems.
• Strong problem-solving and debugging on real-world production problems.
• Experience with Postgres and pgvector.

Responsabilidades

• Implement agent logic, tools, and orchestration against the given architecture
• Build and tune RAG pipelines: ingestion → embeddings → retrieval → re-ranking → evaluation
• Design and optimize Postgres schemas, queries, and vector indexes for production load
• Build the test-generation and test-execution engine for the AI Code Pipeline
• Integrate with Git, CI/CD, and internal services
• Build evaluation harnesses, observability, and guardrails so agents are measurable and safe
• Own the reliability, latency, and cost of the systems you ship
• Write clean, typed, well-tested Python and participate actively in code review

Conocimientos

Python

Async

Typing

CI/CD

Git

LLM systems

Herramientas

Postgres

pgvector

Descripción del empleo

Mondia in Madrid is seeking a software engineer to build production AI agents and related tooling. You will own the agent logic, data layers, and pipelines, delivering reliable, scalable systems for internal use across engineering teams.

You will write clean Python, work on RAG pipelines, Postgres schemas, and integration with Git, CI/CD, and internal services. This role demands hands-on coding, debugging, and collaboration in a high-ownership environment.