AI Systems Engineer

SAGACIFY
Brussels, Belgium
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
Dutch, English, French
Experience level
Senior

Job location

Remote
Brussels, Belgium

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Automation of Tests
Azure
Cloud Computing
Continuous Integration
Cursor (Graphical User Interface Elements)
DevOps
Identity and Access Management
Python
Machine Learning
Open Source Technology
TypeScript
Management of Software Versions
Flask
Large Language Models
FastAPI
Amazon Web Services (AWS)
AI Platforms
Kubernetes
Low Latency
HuggingFace
Machine Learning Operations
Api Design
Amazon Web Services (AWS)
Docker

Job description

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., * 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.

What you'll work with :

Core technologies :

  • Python
  • OpenAI API, Hugging Face Transformers
  • LangChain, LangGraph, Langfuse
  • FastAPI or Flask, Docker, Kubernetes, CI/CD pipelines
  • Cloud GPU
  • AWS (S3, SQS, IAM, RDS, etc.)

Requirements

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., * TypeScript

  • Azure
  • AI-native engineering workflows: hands-on experience using AI coding agents and AI-assisted development environments (Cursor, Claude Code, Windsurf, Copilot, etc.), including context engineering, subagent orchestra…

About you :

  • 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.

Why you will love working with us :

You'll be part of a team of enthusiasts who love to learn and continuously develop skills in different areas and technologies. You'll work with both the Sagacify and Craftzing teams, purposefully driven to create solutions that make a lasting difference, in an environment tailored to your needs.

About the company

Founded as one of the first AI companies in Belgium with a mission to create a meaningful impact, we are believers in automation and efficiency. We see Artificial Intelligence as a toolbox that will allow us to automate more of the growing list of tasks that no longer require human-level cognition. We are a tech team specialising in AI engineering, LLM systems, and MLOps. At Sagacify, part of Craftzing, you will find a collaborative human-sized environment with a great team spirit where you can bring ideas and take responsibilities in the areas you want to evolve in, regardless of your level of experience. We strive to create innovative digital solutions with a lasting impact, in a fun atmosphere where remote work, flexible schedules and regular team events are part of our culture. We are looking for skilled people and team players to join the adventure. Your role : We're on the lookout for a Mid-Level / Senior ML & GenAI Team Lead who is equally at home in pull requests as in people conversations. Someone who does not see leadership and technical depth as a trade-off, but as two things that make each other better. In this role, you will help build and steer a high-performing team of ML and AI Engineers, while staying an active contributor on client projects that actually ship. In practice your time is split roughly between 30% of leading the team and 70% of hands-on delivery. In this role you sit at the intersection of working across teams, offices, and disciplines. You report to the Head of ML at Sagacify and collaborate closely with the Craftzing delivery organisation.

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