Edge AI & Industrial Controls Engineer

Vertiv Group Corporation

Tognana

In loco

EUR 44.000 - 54.000

Tempo pieno

14 giorni+

Generatore di candidature

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Descrizione del lavoro

Vertiv seeks a Controls Software Engineer to join its Piove di Sacco site in Italy. You will design, develop, and maintain Linux-based edge platforms and AI-enabled workflows for industrial control systems, collaborating with firmware, hardware, cloud, and QA teams to ensure reliability.

You will implement Python and C/C++ components, enable distributed device communication (Modbus, MQTT, CAN), and help shape AI-assisted tooling that improves diagnostics, knowledge access, and engineering

Competenze

Degree in a STEM field such as Computer Science, Electronic Engineering, Automation, Physics, or equivalent practical experience.
Strong software engineering skills in Python.
Good working knowledge of C/C++ in systems, embedded, or performance-sensitive environments.
Solid understanding of Linux systems, command-line tooling, process management, networking basics, and Bash scripting.
Experience building modular software components, services, or tooling with maintainability and quality.
Experience with one or more communication technologies such as Modbus, MQTT, CANbus/CANopen, serial protocols, TCP/IP-based device integration, or similar.
Experience with Docker, containerized development environments, or service-based deployment workflows.
Familiarity with CI/CD practices and version control workflows.
Ability to work across disciplines and deal with real-world engineering constraints, incomplete information, and integration complexity.
Fluent English, written and spoken

Mansioni

Design and implement software components and services in Python and C/C++ for Linux-based edge and control platforms.
Develop modular software for distributed embedded and edge systems, including data acquisition, diagnostics, orchestration, and device interaction.
Build and maintain communication and integration layers using protocols such as Modbus RTU/TCP, MQTT, CANbus/CANopen, and similar industrial or field protocols.
Create internal tooling and engineering utilities for configuration, deployment, troubleshooting, validation, and system analysis.
Design and implement AI-assisted and agent-based workflows to improve engineering productivity, diagnostics, knowledge retrieval, and service operations.
Develop software systems that combine LLMs, external tools, APIs, structured data, technical documentation, and workflow logic in a controlled and reliable way.
Translate technical knowledge, interface specifications, and system documentation into machine-usable workflows, structured context, and retrieval pipelines.
Evaluate AI-enabled workflows for correctness, maintainability, observability, safety, and practical engineering usefulness.
Contribute to software architecture decisions, including modularity, interface design, service boundaries, and long-term maintainability.
Write and maintain automation, integration, and deployment tools using Python, Bash, containers, and CI/CD pipelines.
Debug, profile, test, and optimize system behavior across edge software, communications, and supporting services.
Produce and maintain high-quality technical documentation, including module descriptions, interface contracts, workflow definitions, and integration guidance.
Collaborate closely with firmware, hardware, cloud, QA, technical service, and product stakeholders to identify high-value software and AI automation use cases.