Post a aimsiú
Aimsigh an post ceart duitse as na mílte deiseanna atá ar fáil ar fud na hEorpa. Is é EURES - an Tairseach Eorpach um Shoghluaisteacht ó Phost go Chéile - a chuireann na torthaí cuardaigh ar fáil.
We're on the lookout for a Mid-Level AI Systems Engineer who bridges AI engineering and MLOps. Someone who loves getting hands-on with LLMs, agents, and RAG pipelines, and who cares just as much about what happens once a model reaches production as about building it in the first place. In this role, you'll design, build, deploy, and operate production-grade AI systems, with a strong focus on generative AI, LLM-based applications, and reliable machine learning operations. In practice your time is split roughly between 60-70% AI Engineering and 30-40% MLOps.
In this role you sit at the intersection of engineering and operations, working across teams and disciplines. You'll report to the Head of ML at Sagacify and collaborate with the wider Sagacify and Craftzing delivery organisation. A role that can naturally grow towards a Team Lead position over time.
What you'll do :
AI Engineering (60-70%)
- Orchestrate AI system components: LLMs, vector databases, APIs, orchestration layers, and user interfaces
- Develop autonomous agents and conversational systems that can plan actions and interact with external tools or APIs
- Build and optimise RAG pipelines connecting enterprise data sources to LLMs for grounded, contextualised, reliable answers
- Evaluate system quality through generative AI metrics, coherence tests, and production monitoring (latency, API costs, bias)
- Deploy and scale solutions with strong attention to latency, security, reliability and cost efficiency
- Keep an eye on the ecosystem for new models, frameworks and techniques, including open-source tools such as LangChain, LangGraph, Langfuse, etc.
- Perform prompt and context engineering to improve output quality, reduce hallucinations, and manage conversational state effectively
MLOps (30-40%)
- Build and maintain automation for model deployment, including CI/CD pipelines and automated testing
- Continuously monitor model performance in production, including drift detection and quality metric tracking
- Manage updates of libraries, models, and related dependencies in production environments
- Ensure versioning, reproducibility and safe rollout of models and AI services
- Collaborate closely with ML engineers, developers, DevOps and infrastructure teams for smooth delivery
- Stay current with the latest MLOps practices, tools and platform components
You stay in the code, you stay curious about what happens after deployment, and you keep learning as you go.
- You have 3 to 5 years of experience in AI/ML engineering or related fields
- You have a solid understanding of LLM fundamentals: Transformers, attention mechanisms, generation parameters and fine-tuning approaches
- You have strong problem-solving ability and algorithmic creativity
- You communicate clearly with both technical and non-technical stakeholders
- You have a team spirit and enjoy collaborating across multiple roles
- You bring rigour, responsiveness and a good incident-handling mindset
- You're autonomous, curious, and quick to learn new tools
- You can communicate fluently in Dutch, English and French, or at least the first two languages
Don’t worry if you don’t tick every single box, what matters most is the right mindset and a drive to learn. If you think we’re a match, we’d love to hear from you.
- Aansturen en coachen van een team van ±10 medewerkers
- Coördineren van taken binnen order entry, transportplanning, klachtenbehandeling, receptie en webshop
- Zorgen voor duidelijke communicatie en samenwerking binnen het team
- Waken over een correcte en tijdige verwerking van klantorders
- Opvolgen en verbeteren van service levels en klanttevredenheid
- Optimaliseren van processen rond orderverwerking en transport
- Professioneel behandelen en opvolgen van klachten
- Fungeren als aanspreekpunt voor klanten en interne stakeholders
- Eindverantwoordelijkheid voor het magazijn en de operationele werking
- Coördineren van transportplanning en leveringen
- Regelmatige afstemming met productie om leverbetrouwbaarheid te garanderen
- Onderhandelen en afsluiten van contracten met transporteurs
- Nauwe samenwerking met Sales, Productie en Supply Chain
- Oplossen van operationele issues waar nodig
- Bachelor of Master diploma
- Minstens 10 jaar relevante ervaring in customer service, logistiek en/of warehouse management
- Aantoonbare ervaring in people management
- Sterk analytisch en procesmatig denkvermogen
- Hands-on, oplossingsgericht en besluitvaardig
- Uitstekende communicatieve vaardigheden
- Ervaring met ERP-systemen (bij voorkeur Business Central) is een plus
- Proactieve mindset en sterke verantwoordelijkheidszin
Our client is the Luxembourg-based holding company of a major industrial group with operations across multiple countries in Africa. The group is active in manufacturing, distribution, logistics, and industrial operations.
As part of its digital transformation journey, our client is seeking an AI-Assisted Application Developer (Front-End & Back-End) to join its team in Luxembourg and contribute to the development of innovative internal business applications.
Application Development (Front-End & Back-End)
- Gather and document business requirements from end users and internal stakeholders.
- Design and develop user interfaces, server-side logic, databases, and APIs.
- Build web-based solutions such as: portals, dashboards, data entry and activity tracking tools, reporting applications, business calculators
- Ensure code quality through appropriate structure, readability, testing, and documentation.
Integration & Deployment
- Deploy applications into the internal environment in collaboration with the IT Department.
- Contribute to hosting, security, backup, and operational setup activities.
- Integrate authentication mechanisms using Entra ID / Azure, including Single Sign-On (SSO).
Security & Data Protection
- Ensure compliance with GDPR, Swiss data protection regulations, and internal cybersecurity requirements.
- Apply privacy-by-design and security-by-design principles throughout the development lifecycle.
- Implement best practices for: data minimization, access management, secret management, logging and auditing
- Ensure that sensitive or personal data is never exposed to AI coding assistants.
- Maintain appropriate documentation related to data processing and compliance requirements.
Maintenance & Continuous Improvement
- Investigate and resolve application issues.
- Incorporate user feedback and evolving business requirements.
- Maintain application sustainability through proper version control and up-to-date documentation.
Documentation & User Support
- Produce and maintain technical documentation, including: application architecture, technical decisions, deployment procedures, operational guidelines
- Create user-facing documentation such as: user guides, operating procedures, release notes
- Train and support business users in adopting and utilizing applications effectively.
- Gather feedback and provide first-line functional support.
Profile
- Bachelor's degree or equivalent qualification (Associate's to Master's level) in Computer Science, Software Development, Web Development, or a related field.
- Recent graduates and junior candidates are encouraged to apply.
- 5-7 years of professional experience.
- A portfolio, GitHub profile, or demonstrable project examples will be highly valued.
Technical Skills
- Web development: JavaScript / TypeScript, React, HTML / CSS
- Back-end development: Node.js, Basic Python knowledge is a plus
- Databases: SQL, Basic data modeling concepts, SQLite, PostgreSQL, or equivalent solutions
- API development and integration: REST APIs
- Understanding of authentication and Single Sign-On (Entra ID / Azure is a strong advantage; training can be provided)
- Version control using Git and GitHub
- Basic understanding of deployment processes, CI/CD concepts, and networking
- Awareness of application security and data protection principles
- Ability to effectively leverage, review, understand, validate, and improve code generated by AI coding assistants (Claude Code, Codex, or equivalent), while ensuring data confidentiality and security.