We are DEUS EX MACHINA, a cutting-edge AI Systems company specializing in Artificial Intelligence (AI), Machine Learning (ML), and Analytics for the food, nutrition, and life sciences industries. We leverage Generative AI, Large Language Models (LLMs), knowledge graphs, and first-principles simulation to accelerate how products are discovered, formulated, and manufactured, contributing breakthroughs in nutrition, healthcare, and petcare. At the core of our successful track record are our people, our commitment to clients, Fortune 100 organizations and startups, and our desire to make a positive impact through a creative, focused, and collaborative mindset.
About the role
Our products depend on more than a model or a backend service. They require data pipelines, APIs, knowledge systems, agentic workflows, cloud infrastructure, and production software to work as one system. The AI Systems Engineer is responsible for designing and building that system end to end. You will make decisions, write production code, integrate data and AI components, and work on the whole path from raw data to a reliable application. This is a hands-on engineering role for someone who can move across backend, data engineering, AI systems, and architecture without treating them as separate silos.
What you will do
- Build agentic AI systems using LLMs, retrieval, tools, memory, orchestration, and human-in-the-loop patterns; make explicit decisions about when agents are appropriate and when deterministic software is better.
- Work on the implementation of production AI systems across backend services, data infrastructure, agentic workflows, and cloud components.
- Design and build reliable APIs, services, event-driven workflows, and distributed components that connect our applications, models, and data.
- Build and operate data pipelines for structured, unstructured, scientific, and external data, including ingestion, transformation, indexing, lineage, and quality controls.
- Design retrieval and knowledge architectures using relational databases, vector stores, search systems, knowledge graphs, and other data stores as appropriate.
- Turn prototypes into production systems: define interfaces, failure modes, observability, testing, security, performance, and deployment strategy.
- Make and document architectural decisions, including tradeoffs in cost, reliability, maintainability, scalability, and model performance.
- Work directly with data scientists, bioinformaticians, product managers, and other engineers while remaining responsible for the technical integrity of the complete system.
What we are looking for
- Solid software engineering fundamentals and at least 2 years of hands-on experience building production systems in Python, or a comparable language.
- An appetite for simplicity and results-oriented approach to delivery.
- Actual experience working with backend systems, APIs, microservices, and data-intensive applications. You should be able to understand the architecture, not only implement tickets.
- Practical experience building with modern AI systems, including LLM APIs, RAG, embeddings, tool use, agentic workflows, evaluation, and production integration.
- Experience utilizing AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate coding, debugging, and refactoring workflows.
- Hands-on experience working with data engineering tasks: SQL, data modeling, ETL/ELT, pipeline orchestration, data quality, and working with large or heterogeneous datasets.
- Strong English and the ability to explain technical decisions clearly to engineering, product, and scientific teams.
Strong pluses
- Experience with Python and frameworks such as FastAPI, Django, or Flask; PostgreSQL and one or more NoSQL, vector, graph, or search technologies.
- Experience with AWS, Azure, or GCP; Docker and containerized deployments; Kubernetes or other orchestration platforms.
- Experience with knowledge graphs, semantic search, ontology-driven systems, scientific data platforms, or bioinformatics applications.
- Experience evaluating and operating LLM/agent systems in production, including tracing, guardrails, model routing, prompt/version management, and cost/latency optimization.
- Solid understanding of system design: queues, caching, concurrency, storage choices, service boundaries, fault tolerance, observability, and cloud deployment.
What success looks like
- You deliver on major systems from feature ideation through production operation, with few handoffs between backend, data, and AI teams.
- New AI capabilities reach production quickly without sacrificing reliability, testability, security, or maintainability.
- Data, models, agents, and application services behave as one coherent system rather than a collection of disconnected components.
What it's like to work with us:
DEUS EX MACHINA will provide you with the resources and advanced tools necessary to deliver best-in-class results for our clients, in a workplace that inspires collaboration and creativity. Our people are our most important asset, and we strive to provide an environment that promotes both professional growth and work-life balance.
What to expect working at DEUS:
- We offer a competitive monthly gross salary ranging from €1.500 to €3.500, depending on your experience, technical expertise, and overall fit for the role.
- Flexible work schedule.
- Professional and personal development opportunities.
- Private life & health insurance.
- Wellbeing activities.
- Room to experiment, learn, and have fun.
- Peers with big smiles and fascinating ideas.
- A multidisciplinary, multinational team that values trust, autonomy, and innovation.
If the description above sounds like the next step in your career, we look forward to receiving your application. Please apply with your latest CV in English.