CYS_Software Engineer_TP
Pubblicato il 10-10-2026 - Leonardo in Roma
Questa posizione è in Leonardo Il processo di selezione sarà interamente gestito Leonardo. -- # : Leonardo is an international industrial group, among the world's leading companies 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 controlled companies, 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 a list of the main activities foreseen 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) Technical knowledge and 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) Computer 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 Willingness to travel nationally for short periods
Experience with large-scale big data processing, cloud infrastructure projects, ML/AI projects is a plus
Data engineering (Databricks, Snowflake), cloud (AWS/Azure, OpenStack, Kubernetes), streaming (Confluent Certified Developer for Apache Kafka, Flink) certifications 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
- Availability to obtain security clearance 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 --