CYS_Software Engineer_TP

Questa posizione è in Leonardo

Riassunto dell'opportunità 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.

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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

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