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Leonardo · Multiple locations

# CYS_Software Engineer_TP

Multiple locations Software Engineering 

Listed on Leonardo’s official careers site. Posted October 16, 2026. Check that it is still open and apply there.
[Apply on Leonardo’s careers site →](https://leonardocompany.wd3.myworkdayjobs.com/LeonardoCareerSite/job/IT---Genova---Fiumara/CYS-Software-Engineer-TP_R0025058)

[OpenNash Jobs](https://jobs.opennash.com/) / [Leonardo](https://jobs.opennash.com/companies/leonardo/) / CYS_Software Engineer_TP

## Job description

### Job Description

Leonardo è un gruppo industriale internazionale, tra le principali realtà mondiali nell’Aerospazio, Difesa e Sicurezza che realizza capacità tecnologiche multidominio in ambito Elicotteri, Velivoli, Aerostrutture, Elettronica, Cyber Security e Spazio. Con oltre 60.000 dipendenti nel mondo, l’azienda ha una solida presenza industriale in Italia, Regno Unito, Polonia, Stati Uniti, e opera in 150 paesi anche attraverso aziende controllate, joint venture e partecipazioni.

Protagonista dei principali programmi strategici a livello globale, è partner tecnologico e industriale di Governi, Amministrazioni della Difesa, Istituzioni e imprese. All’interno dell’ Area Cyber & Security Solutions, stiamo ricercando un/a Software Engineer per servizi dati, cloud e ML per la nostra sede di Genova / Roma Laurentina. Di seguito l’elenco delle principali attività previste per il ruolo: Sviluppare microservizi per data ingestion, transformation, API exposure e processing

Implementare servizi per batch e streaming data processing con integration tra i due paradigmi Sviluppare API RESTful, GraphQL e gRPC per data access e analytics query execution Implementare servizi per cloud infrastructure management (compute, storage, networking) Sviluppare servizi per orchestration e provisioning di risorse cloud Implementare servizi per security posture monitoring e compliance checking

Sviluppare componenti per cost tracking, resource optimization e billing Implementare servizi per ML lifecycle management (training, evaluation, deployment, monitoring) Sviluppare servizi per model registry, versioning e metadata tracking Sviluppare API per model serving e inference con support per batch e real-time predictions Implementare servizi per feature store management e feature engineering pipelines

Implementare servizi per metadata management e data catalog integration Sviluppare componenti per data quality validation e monitoring Integrare con data lakehouse per unified batch-streaming storage Integrare con cloud providers APIs (OpenStack, AWS, Azure) per multi-cloud scenarios Implementare servizi per disaster recovery automation e backup orchestration Sviluppare Kubernetes operators per custom resource management

Implementare caching strategies e query optimization per performance Sviluppare servizi per data lineage tracking e impact analysis Implementare servizi per model monitoring (drift detection, performance tracking, data quality) Sviluppare servizi per automated retraining pipelines e continuous learning Garantire scalabilità, reliability e security per data services, cloud services e ML workloads

Implementare pattern per fault tolerance, retry mechanisms e error handling Implementare testing automation e CI/CD pipelines per cloud services, data services e ML pipelines Mantenere elevati standard di qualità del codice attraverso testing e code review Collaborare con data engineers, infrastructure team, data scientists e ML engineers per implementazione end-to-end Titolo di studio Laurea in Ingegneria Informatica, Informatica o equivalente.

Seniority Expert (da 2 a 5 anni di esperienza nel ruolo, o più di 5 anni di esperienza in ruoli analoghi) Conoscenze e competenze tecniche Sviluppo backend con linguaggi enterprise (Java, Python, Scala, Go) per data platforms, cloud platforms e ML platforms Data processing con framework moderni (Apache Spark, Apache Flink) Architetture event-driven per data streaming e real-time processing Cloud platforms APIs (OpenStack, AWS/Azure SDKs) e resource management Kubernetes e container orchestration con operators pattern Infrastructure as Code (Terraform, Pulumi) e automation Microservizi cloud-native con service mesh integration MLOps practices per model lifecycle automation
- Model serving frameworks (TensorFlow Serving, TorchServe, Triton Inference Server) ML orchestration tools (Kubeflow, MLflow) e experiment tracking Feature stores (Feast, Tecton) e feature engineering pipelines Sviluppo di API (RESTful, GraphQL, gRPC) per data services, infrastructure services e ML services Database relazionali e NoSQL ottimizzati per analytics (columnar, document, wide-column) Data lakehouse integration (Delta Lake, Apache Iceberg) con ACID semantics Security automation (policy enforcement, compliance scanning, secrets management) Caching distribuito (Redis, Memcached) per performance optimization API design per infrastructure services e ML services con versioning e backward compatibility Competenze comportamentali Autonomia nella gestione di task complessi multi-componente Buone capacità comunicative e problem solving analitico Orientamento alla qualità del codice, data quality, automazione, infrastructure as code, performance e scalability Security mindset per cloud environments Collaborazione efficace in team cross-funzionali (backend, data engineering, analytics, infrastructure, ML) Proattività nel knowledge sharing e continuous improvement Conoscenze linguistiche Italiano madrelingua, Inglese professionale (B2) Competenze informatiche Linguaggi backend (Java, Python, Scala, Go) e framework (Spring Boot, FastAPI) Apache Spark (PySpark, Scala) per distributed data processing Apache Flink for stream processing (DataStream API, Table API) Event streaming (Apache Kafka) e message brokers Cloud platforms (OpenStack, integration con AWS/Azure) Kubernetes avanzato (operators, CRDs, admission controllers, GPU support con NVIDIA GPU Operator) Infrastructure as Code (Terraform, Ansible, Pulumi) ML frameworks (TensorFlow, PyTorch) e model formats (ONNX, SavedModel)
- Model serving (TensorFlow Serving, TorchServe, Triton) MLOps tools (Kubeflow, MLflow, DVC) Feature stores (Feast) e data versioning Containerizzazione (Docker) e deployment su Kubernetes Database relazionali (PostgreSQL), NoSQL (MongoDB, Cassandra), columnar (ClickHouse), time-series (TimescaleDB) Data lakehouse platforms (Delta Lake, Apache Iceberg) Cache distribuito (Redis) e query optimization Security tools (Vault, OPA, Falco) per cloud security API design e versioning strategies Pipeline CI/CD e monitoring (Prometheus, Grafana) per data applications, cloud services e ML systems Altro Disponibilità a brevi trasferte su territorio nazionale Esperienza con big data processing su larga scala, progetti cloud infrastructure, progetti ML/AI è un plus Certificazioni data engineering (Databricks, Snowflake), cloud (AWS/Azure, OpenStack, Kubernetes), streaming (Confluent Certified Developer for Apache Kafka, Flink) sono titoli preferenziali Conoscenza di data warehousing, OLAP, data modeling, analytics, ML algorithms, data science è un plus Background in progetti data-intensive, system administration, SRE, distributed systems o high-performance computing è un plus Disponibilità a ottenere clearance di sicurezza Seniority: Expert Primary Location: IT - Genova - Fiumara Additional Locations: IT - Roma - Via Laurentina Contract Type: Permanent Total Base Pay Range: 36k-50k Hybrid Working: Hybrid

## At a glance
- Posted by the employer: Oct 16, 2026
- First seen by OpenNash: Oct 13, 2026
- Last checked: Oct 20, 2026
- Listed for: 7 days
- Location: Multiple locations[Apply on Leonardo’s careers site →](https://leonardocompany.wd3.myworkdayjobs.com/LeonardoCareerSite/job/IT---Genova---Fiumara/CYS-Software-Engineer-TP_R0025058)

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