Artificial Intelligence Engineer at Keyrus

Switzerland, Manitoba, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

18 Dec, 26

Salary

90000.0

Posted On

19 Sep, 26

Experience

12 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Industry

Information Technology & Services

Description

For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating.

At Keyrus, you will not just develop skills — you will develop judgment. Your expertise sharpens with every system you architect, every client challenge you solve, and every deployment that compounds on the last.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data, AI, and human decision-making at scale, across industries and geographies. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

Role Details

📍 Job location: Zaandam, Netherlands (Hybrid – 2 days on-site/week)

🕒 Contract type: Freelance / B2B Contract – 12 months

🗓 Target start date: ASAP

⏰ Working hours: Full-time

💵 Compensation: Up to 480 EUR per day

📋 What You'll Architect

As an AI Engineer, you will help organisations transform complexity into measurable outcomes by combining technology, data, intelligence, and human decision-making.

You’ll play a key role in designing, building, and deploying enterprise-grade AI solutions, turning advanced technologies such as Large Language Models, Retrieval-Augmented Generation (RAG), and Agentic AI into reliable, scalable applications that deliver real business value.

This role is both hands-on and technical leadership-oriented — perfect for an experienced engineer who can move comfortably from architecture and solution design to coding, deployment, and mentoring other engineers.

You will:

Design and develop scalable enterprise AI architectures for LLM, RAG, and Agentic AI applications.
Build production-ready AI applications using Python, LangChain, REST APIs, and microservices.
Develop and integrate LLM-powered solutions, including RAG pipelines, AI agents, and supporting services.
Design solutions that are secure, maintainable, scalable, and fit for enterprise environments.
Work with Azure, Docker, Kubernetes, PostgreSQL, and pgvector to deploy and operate AI solutions.
Contribute to technical decisions around architecture, frameworks, APIs, data, infrastructure, and deployment.
Drive engineering quality through code reviews, technical guidance, and mentoring of other engineers.
Collaborate with multidisciplinary teams and stakeholders to translate business requirements into effective technical solutions.
Support delivery through CI/CD, Agile development practices, testing, and continuous improvement.

👤 Who You Are

You are curious, analytical, and motivated by solving meaningful business challenges.
You enjoy turning complexity into clarity and action.
You balance technical thinking with business understanding.
You are comfortable working in collaborative and international environments.
You take ownership of your work and follow through on commitments.
You value continuous learning and are motivated by long-term professional growth.
You communicate clearly and effectively with a variety of stakeholders.

🛠️ What You Bring

Qualifications & Experience

6–10 years of professional software engineering experience.
2–5 years of hands-on experience building and deploying AI/LLM applications in production environments.
Strong experience designing and implementing enterprise-grade AI solutions and architectures.
Proven experience taking AI solutions from development through to production.
Experience working in Agile, collaborative, and engineering-focused environments.
Professional proficiency in English.

Technical & Professional Skills

Strong hands-on programming skills in Python.
Solid experience with Large Language Models (LLMs), RAG, and Agentic AI.
Practical experience with LangChain or similar AI orchestration frameworks.
Strong understanding of REST APIs and microservices architectures.
Experience with Microsoft Azure and cloud-based solution development.
Hands-on experience with Docker and Kubernetes.
Experience with PostgreSQL and pgvector or similar vector database technologies.
Strong understanding of AI application architecture, scalability, integration, and production deployment.
Experience with CI/CD pipelines, automated testing, and modern software engineering practices.
Strong problem-solving and analytical capabilities, with the ability to turn complex technical challenges into practical solutions.
Ability to communicate technical concepts clearly and collaborate effectively with both technical and non-technical stakeholders.
Experience conducting code reviews and mentoring engineers.

Nice to Have

Experience in consulting or client-facing environments.
Experience designing AI platforms or solutions for large enterprise environments.
Knowledge of cloud-native AI/ML services and MLOps practices.
Experience with additional LLM orchestration, agent frameworks, or AI development platforms.
Exposure to international projects or multicultural engineering teams.
Relevant cloud, AI, or software engineering certifications.

Responsibilities