AI Software Engineer 100% (f/m/d)

Julius Baer is hiring an AI Software Engineer 100% (f/m/d) in Madrid, Spain. Level rates it ; you can apply on Julius Baer.

Level's read on this job

On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include RAG and MLOps.
Level classifies it as a mid-level role.
Level lists 197 other open roles at Julius Baer.
The role was posted in the last few days.

AI in this role

ragml-ops

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth.
Let’s shape the future of wealth management together.

YOUR CHALLENGE

Own the engineering and integration layer of AI capabilities into the software delivery toolchain, ensuring secure, scalable, and maintainable delivery of AI solutions through automation and collaboration with platform teams
Collaborate closely with AI Product Engineers and platform teams to define and scope opportunities for AI-driven innovation
Prototype and validate Large Language Model (LLM)-based or retrieval-augmented generation (RAG) pipelines to drive business value
Contribute to AI-driven automation efforts across developer productivity platforms, enhancing efficiency and effectiveness
Develop and maintain APIs, pipelines, and service integrations for AI features within existing platforms, such as CI/CD, observability, and developer workplace
Ensure traceability, logging, and compliance of integrated solutions, adhering to enterprise standards and security best practices
Drive best practices for automation, monitoring, and reproducibility, promoting a culture of continuous improvement

YOUR PROFILE

2-4 years of experience as a Software Engineer, but with a strong background in AI integration and automation
Strong knowledge of DevOps/MLOps, CI/CD pipelines, Cloud environments, containerization (Docker/K8s), and APIs.
Experience integrating Machine Learning (ML) and Generative AI components into production systems, with a focus on scalability, security, and maintainability
Security-aware and familiar with enterprise standards for tooling, ensuring the highest levels of data protection and compliance
Comfortable working in agile and cross-functional teams, with excellent communication and collaboration skills
Master or Bachelor in Computer Science or a related area, or proven relevant working experience
Very good English level

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How we rate this

AI Software Engineer 100% (f/m/d) at Julius Baer rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Software Engineer 100% (f/m/d) is an open job at Julius Baer.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Madrid.
The job was posted on November 5, 2026.
Seniority: mid.
Applications are handled by Julius Baer. Apply on Julius Baer

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML Ops

Also common in software engineer jobs at this level

Python C++AWS AI agents Java TypeScript

Pay

Typical software engineer job: $167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG and ML Ops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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