AI Systems Engineer
- Compensation
- Not disclosed
- Location
- Thessaloniki/Athens/Remote, -, Greece
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 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.
Full description
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.