About the company.
We are an Italian company specialized in applied Artificial Intelligence. Our mission is to design and build new AI-based solutions, from early pilots to MVPs, together with demanding enterprise clients. We work on complex problems where AI is the core of the solution, and where reliability, explainability, and control is essential.
About the R&D unit.
Within the company, the R&D unit acts as an AI engineering lab. The team explores new AI capabilities and usage scenarios and transforms them into running systems that can be demonstrated, evaluated, and evolved.
Key characteristics of our R&D work.
* Projects built around advanced AI components and AI-native architectures.
* Multiple short, parallel initiatives instead of one long product stream.
* Starting from open, ambiguous problem statements and shaping them into concrete system designs.
* Intensive use of open-source technologies often extended or adapted for our needs.
* Prototypes that run as complete systems and clearly demonstrate value in controlled environments.
The outcome of our work is a set of robust, well-structured AI services and pipelines that can be tested internally, presented to clients, and, when validated, evolved into full-scale solutions by production-oriented teams.
Role overview.
We are looking for an R&D Backend & AI Systems Engineer to strengthen this R&D unit. The role focuses on building and integrating AI-based services and APIs, transforming experimental ideas and components into reliable, usable systems.
You will collaborate closely with other R&D engineers who design AI pipelines and models. Your responsibility is to give these components a solid engineering shape: clear interfaces, strong contracts, predictable runtime behaviour, and the necessary control mechanisms to use AI safely and effectively.
Your work will be central in:
- Designing and implementing the service layer around AI components.
- Defining how different modules connect and exchange data.
- Turning experimental elements into coherent, testable systems suitable for pilots and pre-MVP stages.
What you will work on.
In this role you will typically:
* Design and implement API layers around AI components: Create HTTP/JSON APIs for LLM-based services, retrieval and reasoning modules, and in-house models, with clearly defined contracts and behaviors.
* Build and evolve AI service gateways and orchestration: Implement routing, composition, and coordination for multiple AI services and pipelines, including request flow, prioritisation, and fallback paths.
* Define and enforce schemas and contracts: Use explicit models and validation rules for all inputs and outputs, handle errors consistently, and keep AI behavior within agreed limits.
* Encapsulate models into controllable services: Wrap local and cloud-based models into services with clear responsibilities, configuration, rate limits, and safeguards.
* Integrate and extend open-source components: Work with modern AI frameworks, libraries, and tools; select and integrate them into our systems, and when useful, adapt or patch them.
* Make prototypes deployable as systems: Ensure that each prototype can be deployed as a small but complete system that demonstrates business value in a controlled environment and is ready for further industrialization.
Why this role is attractive.
* AI-centric engineering: You work at the heart of AI systems, where creating robust, controllable services is as important as the models themselves.
* Variety and pace: You contribute to several short, intense R&D initiatives rather than a single long project, with continuous exposure to new domains and ideas.
* Impact on architecture: You influence how new AI solutions are shaped from day one, designing the service and integration patterns that others will build on.
* Collaborative environment: You join a compact, high-level R&D team and interact with other expert groups in the company, keeping strong ownership on your systems.
* Clear path from idea to MVP: You see the full journey from initial concept to running prototype and pre-MVP, and your engineering work is a key enabler for that journey.
Technical environment.
Our core environment combines modern backend engineering with the contemporary AI stack.
* Python as the primary implementation language.
* Modern web frameworks for APIs (e.g. FastAPI or similar).
* API gateways, routing components, and orchestration logic for multiple backend services.
* Schema-based request/response validation (e.g. Pydantic models or equivalent).
* Integration with AI models, including large language models and other neural components, both on-premise and in the cloud.
* Use of ontologies and structured representations to manage and interpret AI outputs.
* AI orchestration and tooling (e.g. LangChain, LangGraph or similar frameworks).
* Standard data-layer and messaging components to support AI workflows (e.g. relational databases, caches, queues, background workers).
* Containerization for deployment in R&D and demo environments.
Candidate profile.
We are looking for an engineer who:
* Enjoys designing and building backend services and APIs and cares about clean, well-structured code.
* Has solid experience with Python-based backend development and modern API frameworks.
* Understands how AI-based components behave at runtime and how to integrate them into larger systems.
* Is comfortable defining data models, schemas, and contracts and enforcing them through validation and testing.
* Thinks in terms of systems: components, boundaries, flows, reliability, observability.
* Likes working with open problems, iterating from rough concept to running solution.
* Communicates clearly with colleagues from different backgrounds and can align technical decisions with project goals.
* Is motivated by building new things and seeing them run in realistic conditions with real users and stakeholders.