Questa posizione è in Leonardo Riassunto dell'occasione da parte della Joinrs AI : Leonardo ricerca un Software Engineer esperto con laurea in Ingegneria Informatica, Informatica o equivalente .

Il ruolo prevede lo sviluppo di microservizi, gestione cloud e servizi ML in un contesto multidisciplinare. Offerta a tempo pieno con sede a Genova o Roma in modalità ibrida. Disponibilità per brevi trasferte nazionali è richiesta.

Il processo di selezione sarà interamente gestito da Leonardo. Questa opportunità è disponibile su Genova, Roma. Leonardo is an international industrial group, among the leading global players in Aerospace, Defense and Security, which creates multi-domain technological capabilities in Helicopters, Aircraft, Aerostructures, Electronics, Cyber Security and Space.

With over 60,000 employees worldwide, the company has a solid industrial presence in Italy, the United Kingdom, Poland, the United States, and operates in 150 countries also through subsidiaries, joint ventures and shareholdings. A protagonist in the main strategic programs at a global level, it is a technological and industrial partner of Governments, Defense Administrations, Institutions and companies. Within the Cyber & Security Solutions Area , we are looking for a Software Engineer for data, cloud and ML services for our Genoa / Rome Laurentina office.

Below is the list of main activities envisaged for the role: Develop microservices for data ingestion, transformation, API exposure and processing Implement services for batch and streaming data processing with integration between the two paradigms Develop RESTful, GraphQL and gRPC APIs for data access and analytics query execution Implement services for cloud infrastructure management (compute, storage, networking) Develop services for orchestration and provisioning of cloud resources Implement services for security posture monitoring and compliance checking Develop components for cost tracking, resource optimization and billing Implement services for ML lifecycle management (training, evaluation, deployment, monitoring) Develop services for model registry, versioning and metadata tracking Develop APIs for model serving and inference with support for batch and real-time predictions Implement services for feature store management and feature engineering pipelines Implement services for metadata management and data catalog integration Develop components for data quality validation and monitoring Integrate with data lakehouse for unified batch-streaming storage Integrate with cloud providers APIs (OpenStack, AWS, Azure)



for multi-cloud scenarios Implement services for disaster recovery automation and backup orchestration Develop Kubernetes operators for custom resource management Implement caching strategies and query optimization for performance Develop services for data lineage tracking and impact analysis Implement services for model monitoring (drift detection, performance tracking, data quality) Develop services for automated retraining pipelines and continuous learning Ensure scalability, reliability and security for data services, cloud services and ML workloads Implement patterns for fault tolerance, retry mechanisms and error handling Implement testing automation and CI/CD pipelines for cloud services, data services and ML pipelines Maintain high code quality standards through testing and code review Collaborate with data engineers, infrastructure team, data scientists and ML engineers for end-to-end implementation Education Degree in Computer Engineering, Computer Science or equivalent.

Seniority

Expert (2 to 5 years of experience in the role, or more than 5 years of experience in similar roles) Knowledge and technical skills Backend development with enterprise languages (Java, Python, Scala, Go) for data platforms, cloud platforms and ML platforms Data processing with modern frameworks (Apache Spark, Apache Flink) Event-driven architectures for data streaming and real-time processing Cloud platforms APIs (OpenStack, AWS/Azure SDKs) and resource management Kubernetes and container orchestration with operators pattern Infrastructure as Code (Terraform, Pulumi) and automation Cloud-native microservices with service mesh integration MLOps practices for model lifecycle automation Model serving frameworks (TensorFlow Serving, TorchServe, Triton Inference Server) ML orchestration tools (Kubeflow, MLflow) and experiment tracking Feature stores (Feast, Tecton) and feature engineering pipelines API development (RESTful, GraphQL, gRPC) for data services, infrastructure services and ML services Relational and NoSQL databases optimized for analytics (columnar, document, wide-column) Data lakehouse integration (Delta Lake, Apache Iceberg) with ACID semantics Security automation (policy enforcement, compliance scanning, secrets management) Distributed caching (Redis, Memcached)



for performance optimization API design for infrastructure services and ML services with versioning and backward compatibility Behavioral skills Autonomy in managing complex multi-component tasks Good communication skills and analytical problem solving Orientation towards code quality, data quality, automation, infrastructure as code, performance and scalability Security mindset for cloud environments Effective collaboration in cross-functional teams (backend, data engineering, analytics, infrastructure, ML) Proactivity in knowledge sharing and continuous improvement Language skills Native Italian, Professional English (B2) IT skills Backend languages (Java, Python, Scala, Go) and frameworks (Spring Boot, FastAPI) Apache Spark (PySpark, Scala) for distributed data processing Apache Flink for stream processing (DataStream API, Table API) Event streaming (Apache Kafka) and message brokers Cloud platforms (OpenStack, integration with AWS/Azure) Advanced Kubernetes (operators, CRDs, admission controllers, GPU support with NVIDIA GPU Operator) Infrastructure as Code (Terraform, Ansible, Pulumi) ML frameworks (TensorFlow, PyTorch) and model formats (ONNX, SavedModel) Model serving (TensorFlow Serving, TorchServe, Triton) MLOps tools (Kubeflow, MLflow, DVC) Feature stores (Feast) and data versioning Containerization (Docker) and deployment on Kubernetes Relational databases (PostgreSQL), NoSQL (MongoDB, Cassandra), columnar (ClickHouse), time-series (TimescaleDB) Data lakehouse platforms (Delta Lake, Apache Iceberg) Distributed cache (Redis) and query optimization Security tools (Vault, OPA, Falco) for cloud security API design and versioning strategies CI/CD pipelines and monitoring (Prometheus, Grafana) for data applications, cloud services and ML systems Other Availability for short national business trips Experience with large-scale big data processing, cloud infrastructure projects, ML/AI projects is a plus Data engineering certifications (Databricks, Snowflake), cloud (AWS/Azure, OpenStack, Kubernetes), streaming (Confluent Certified Developer for Apache Kafka, Flink) are preferred qualifications Knowledge of data warehousing, OLAP, data modeling, analytics, ML algorithms, data science is a plus Background in data-intensive projects, system administration, SRE, distributed systems or high-performance computing is a plus Willingness to obtain security clearance Seniority: Esperto Primary Location: IT - Genova - Fiumara Additional Locations: IT - Roma - Via Laurentina Contract Type: Permanent Hybrid Working: Ibrido [LI-REMOTE] [J-MCITY]

📌 CYS_Software Engineer_TP (Genova)
🏢 Leonardo
📍 Genova