Full-Stack Developer

We are looking for a Full-Stack Developer to join Zerynth Product Development , the team responsible for building and evolving the Zerynth Industrial AI Copilot Platform - a cloud and edge‑native system designed to digitalize industrial operations and enable AI‑driven decision‑making on real shopfloors. The platform operates at the intersection of industrial machinery, cloud infrastructure, and artificial intelligence , ingesting large volumes of data from connected machines and transforming them into actionable insights and intelligent interactions. In this role, you will work across the full stack—frontend, backend, data pipelines, and infrastructure—contributing to a platform that is mission‑critical for our customers . You will also play an active role in the development of Zero , our Industrial AI Copilot, building LLM/RAG‑based components and intelligent agents that interact with industrial data, guide users, and automate operational tasks. Given the critical nature of industrial environments and evolving regulatory requirements (e.g. NIS2 ), security, reliability, and resilience are core design principles of the platform , not optional features. We are looking for a pragmatic and curious engineer/computer scientist, comfortable navigating different technologies (Go, React, Python, containers, distributed systems), and motivated to work on complex, real‑world industrial challenges. Your mission You will build the core of an Industrial AI platform used in real production environments . You will work in a team where engineering drives product evolution , through prototypes and concrete solutions. You will gain hands‑on experience with AI applied to industrial data , not toy use cases. You will contribute to systems where reliability, security, and impact truly matter . What you will do: Design, develop, and maintain backend services (Go) and frontend applications (React/TypeScript) of the Zerynth platform. Build scalable, secure, and cloud‑native architectures for industrial data ingestion, processing, and visualization. Develop and integrate LLM‑based agents, RAG pipelines, and AI components within the Industrial AI Copilot. Collaborate with the team to define solutions through rapid prototyping and technical exploration, rather than heavy upfront documentation. Contribute to data pipelines, message‑driven architectures, and distributed systems handling industrial‑scale workloads. Implement and maintain CI/CD pipelines and automated deployment processes. Ensure observability, reliability, and operational robustness of the platform. Apply security‑by‑design principles across services, APIs, and infrastructure. Continuously improve performance, scalability, and developer experience. What skills we need: -At least 3 years of practical experience (internships, thesis projects, or professional experience) Languages & Frameworks Go React (or equivalent frontend frameworks) Python Systems & Networking Linux (Ubuntu/Debian): administration and troubleshooting Databases & Data Management Communication Protocols HTTP / HTTPS MQTT / MQTTS DevOps, Reliability & Security Docker and container‑based deployments Reverse proxies and load balancers (Nginx, HAProxy, or equivalents) CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) Observability stacks (Prometheus, Grafana, Loki, ELK) Security fundamentals (mandatory awareness) Secure authentication and authorization mechanisms TLS, certificate management, and secure communications Basic secure‑by‑design software principles Awareness of availability, integrity, and data protection requirements in industrial and mission‑critical systems Strong proficiency with Git and modern branching strategies (GitFlow, trunk‑based) Ability to work effectively in distributed and cross‑functional teams Languages Excellent Italian (written and spoken) Excellent English (written and spoken) Bonus skills (a plus, but not mandatory) AI & LLM Development Familiarity with Large Language Models and prompt engineering Experience developing AI copilots or intelligent assistants Knowledge of LLM agent frameworks (LangChain, Semantic Kernel, NetGraph, or equivalents) Integration of AI models into cloud‑native architectures (REST/gRPC, microservices) Experience with data processing pipelines and model fine‑tuning (including API‑based models) Familiarity with ML/AI frameworks (PyTorch, TensorFlow) Awareness of AI safety, monitoring, and responsible AI practices Security, Compliance & Industrial Context Experience or interest in cybersecurity best practices for cloud and industrial systems Understanding of OT/IT security boundaries and common threat models Secure API design, secrets management, and role‑based access control Awareness of regulatory and compliance frameworks affecting industrial platforms (e.g. NIS2, operational resilience, data protection) Interest in security monitoring, incident response, and system hardening Experience with high‑availability and fault‑tolerant architectures in critical environments Infrastructure & Automation Infrastructure as Code (Terraform) Infrastructure and configuration automation (Ansible or equivalent) Application process Candidates will have a first interview. If successful, they will proceed to a skill assessment phase. Contractual offer RAL range: €30,000–€36,000, commensurate with experience The onboarding requires presence at our Pisa office; once completed, flexible work options are available. About Zerynth Zerynth is revolutionizing industrial manufacturing with a Copilot Platform that integrates IoT and Artificial Intelligence, making digital transformation simple, fast, and secure for any production process. Our mission is to help manufacturing companies operate more efficiently by leveraging real‑time data, strategic KPIs, and proactive maintenance. Zero, our conversational AI agent, provides instant access to data through chat, automatically generating insights, notifications, and reports. The platform integrates seamlessly with ERP, MES, and BI systems, enriching them with accurate operational data for improved planning. Zerynth offers a structured approach—from process mapping and asset connectivity to continuous AI training with certified expert support. The results speak for themselves: up to 70% reduction in machine downtime, 40% less energy consumption, and 30% lower maintenance costs. Founded in Pisa in 2015, Zerynth now works with over 200 industrial companies. #J-18808-Ljbffr