ShopFully · Italy

We are the platform turning browsing into shopping . We connect 200 million shoppers with deals they love while boosting local sales for hundreds of top retailers and brands. We help consumers save time and money while making smart shopping decisions, and we support retailers and brands in engaging customers from online research to in-store purchases. In 2024, Shopfully joined forces with the North American company Flipp , creating a global leader in the sector. Together, we reach 400 million households and serve over 1,000 top retailers and brands across 27 markets, including Europe, Canada, the USA, Latin America, and Australia. Ready to  spark your growth with us? WHO WE LOOK FOR 🦄 We are looking for a Senior Machine Learning Engineer to join our Audience Platform team within Ad Products. In this role, you will own and extend both the machine learning systems and the corresponding backend infrastructure that power 1P, 2P, and 3P audience data across Flipp and Shopfully. This is an engineering-first role for someone who builds and operates production ML systems end-to-end—not a research scientist handing off code to someone else to productionize. You bring hands-on comfort with statistics, model selection, building, tuning, and experiment design, combined with strong software engineering fundamentals to build scalable pipelines on core tables running into tens of billions of rows. If you are passionate about MLOps, scalable feature engineering, and shipping production ML systems that drive measurable business impact, this role is for you!   WHAT YOU WILL DO 🏄 End-to-End ML Systems Ownership: Design, build, deploy, and monitor production ML models and pipelines—such as the IAB Segmentation Model, Retailer & Category Affinity Segments, and Custom Segment Toolkits.   Feature & Data Engineering at Scale: Build and maintain high-volume feature engineering and data pipelines using Spark, Databricks, Python, and SQL, working with core tables containing tens of billions of rows.   MLOps & Model Lifecycle Management: Implement robust MLOps practices, including model registries, offline/online evaluation, experiment tracking (MLflow or equivalent), and monitoring for data/model drift and quality.   Audience Platform Integration: Collaborate on the platform side (Audience API, User Profile API, Kafka Topics, and activation integrations like DV360, Braze, and TTD) to ensure models seamlessly integrate into downstream production services.   Experimentation & Model Tuning: Design and execute offline evaluations and A/B tests to validate modeling impact, optimize hyperparameters, and unlock new data signals (e.g., Store Trip Data).   Privacy & Compliance: Plan and execute modeling and data pipeline initiatives in strict accordance with data regulatory laws (GDPR, CCPA, consent management).   Cross-Functional Collaboration & AI Workflows: Partner with Product Analytics, Marketing Science, Data Engineers, and Software Engineers to drive revenue OKRs. Utilize AI-assisted development tools (e.g., Cursor, Claude Code) to maximize daily throughput.   WHAT YOU WILL NEED 🪄 Strong Software Engineering Fundamentals: Comfortable owning and operating production backend/data systems end-to-end, including participating in the team's on-call rotation.   End-to-End Production ML Track Record: Proven experience across the full ML lifecycle: feature engineering on Databricks/Spark, model training, evaluation, deployment, and monitoring in production.   Genuine Modeling & Statistics Skills: Ability to build, tune, and evaluate models from scratch, with solid grounding in statistics, hyperparameter tuning, and experiment design (A/B testing).  Data Scale & Tech Stack Mastery: Strong proficiency in Python, Spark, SQL, and Databricks. Comfort with distributed data pipelines at real scale.   MLOps Fluency: Experience with ML lifecycle tools (MLflow or equivalent), model registries, and production monitoring for drift/quality.   Active Use of AI Coding Agents: Hands-on use of AI development tools (e.g., Cursor, Claude Code) to increase personal engineering throughput.   Education: Bachelor's degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative field.   Fluent in English: Strong written and spoken communication skills with overlap availability into North American hours (9am to 12pm EST)   👉 At our company, we value diversity and actively encourage it — we believe a variety of perspectives and backgrounds makes us stronger. We focus on potential rather than on having a “perfect” CV. If this role excites you and you believe you could grow into it — even if you don’t tick every single box in the requirements — we’d love to hear from you! NICE TO HAVE  🎆 Ad-tech or programmatic advertising context.   Privacy engineering background (GDPR, CCPA).   Deep Databricks platform administration knowledge.   Familiarity with LLM platforms (OpenAI, Gemini) and embedding research. SALARY RANGE ⚖️ : €50,000 – €70,000 fixed gross salary per year.   LOCATION 🌐   While we have offices in Milan , Barcelona and Sofia , you can benefit from our flexible hybrid model, empowering you to work where you’re most effective in Europe. Full remote available from Europe.   WHAT YOU WILL FIND AT SHOPFULLY 🤗 🌎 An opportunity to thrive in a rapidly scaling multinational company 🕶️ A vibrant, informal, and inclusive work environment 🧠 We champion autonomy, flexibility, and a hybrid work model, empowering you to own your work 📚 Access to learning opportunities and regular feedback sessions 🍓 Enjoy our central, modern offices featuring fresh snacks, coffee (including vegan options!), and ergonomic setups 🎉 Engage in meaningful team events: offsites, happy hours, company parties and celebrations that unite us beyond daily tasks 💻We provide all the necessary equipment for you to work effectively and set up your workspace, wherever you are 🧰 Benefit from additional country-specific advantages based on local contracts and practices   WHO WE ARE 💜  We’re a team of 450 people (and counting!), from 30 different nationalities. We’re on a mission to innovate, and we believe the key to that is seeing the world through a variety of perspectives. That’s why building a more diverse team, as well as bringing in even more talent, is so important for us.   TO FEEL AT HOME 🛋️ IN SHOPFULLY YOU NEED 🎯 Progress Over Perfection : We move forward. Always. In a fast-moving world, speed with purpose beats certainty without action. Momentum matters—not for its own sake, but because it drives results. Clarity Through Transparency : We bring each other along. We work in teams, not silos. Transparency gives context, and context enables action. That means we share decisions early, publish work in progress, and document outcomes so others can learn, move faster, and build better. Learn Loudly : We grow by doing and by daring. Big bets unlock big breakthroughs. But real innovation demands risk, and risk always carries the possibility of failure. That’s not a flaw. It’s the price of ambition. Challenge with Empathy : We speak up, even when it’s hard—because candor shows care, and leads to better outcomes. Listening deeply is how we grow. Disagreeing openly is how we build trust. Always Build Better: We are builders—of products, systems, and ideas. But more than that, we are builders of better. Better has no finish line. It’s a mindset. If you choose to apply for this specific job position and submit your application, which may include personal data such as your identifying details, contact information, curriculum vitae, cover letter, professional qualifications, and/or employment history, please be informed that your data may be shared with our Affiliates*, including Offerista Group GmbH and Flipp Operations Inc. The aforementioned entities will act as joint controllers for the limited purpose of intra-group sharing related to the evaluation of candidates’ applications. This means that your data may be processed by the Affiliate to assess your application and, if deemed suitable, to contact you regarding potential employment opportunities. However, please note that from the moment an Affiliate initiates direct contact with you and engages in any further processing of your personal data beyond the initial intra-group sharing for evaluation purposes, such Affiliate shall act as an independent data controller. In such cases, the processing of your personal data will be subject to the specific privacy policies that can be found  here. * Affiliates shall mean any entity that directly or indirectly controls, is controlled by or is under common control with ShopFully SpA and its Affiliates’ subsidiaries, meaning any entity which is directly or indirectly controlled by the Affiliates.

Leonardo · Genova - Fiumara, Italy

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

Leonardo · Roma - Via Laurentina, Italy

Job Description: Leonardo SpA 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 DevSecOps Engineer per gestione infrastruttura e CI/CD per la nostra sede di Genova / Roma Laurentina. La persona si occuperà delle seguenti attività: la risorsa sarà responsabile della progettazione, implementazione e gestione di pipeline CI/CD sicure e automatizzate su un portfolio multi-prodotto, operando in stretta collaborazione con CTO, Product Manager, PEM e team di sviluppo. Il perimetro di azione copre l’intero ciclo di vita del software: dal branching governance al rilascio controllato in produzione, dall’integrazione dei controlli di sicurezza automatizzati al monitoraggio continuo della postura di sicurezza dei prodotti. In particolare, si occuperà di: Progettare, implementare e mantenere pipeline CI/CD su un portfolio di circa 20+ prodotti, garantendo automazione, ripetibilità e tracciabilità end-to-end dei rilasci, dalla build alla promozione in produzione. Definire e governare le strategie di branching (GitFlow, trunk-based development, release branching) sull’intero portfolio di prodotti, garantendo coerenza nelle policy di merge request, tagging semantico (SemVer) e promozione delle versioni attraverso gli ambienti di integrazione, test e produzione. Mantenere la mappatura aggiornata delle versioni di prodotto e di soluzione, tracciando per ogni release la versione puntuale di tutti i sotto-moduli, librerie, dipendenze e tool di build, in modo che ogni deliverable sia ricostruibile e verificabile a partire da un insieme ben definito e documentato di componenti. Integrare controlli di sicurezza automatizzati nelle pipeline (SAST, DAST, SCA, container scanning, secret detection), assicurando che ogni artefatto sia analizzato e validato prima di ogni promozione ambientale. Pianificare ed eseguire sessioni sistematiche di vulnerability assessment sul software di prodotto: avvalendosi di Dependency-Track o simili, per il monitoraggio continuo delle vulnerabilità nelle dipendenze (CVE tracking, SBOM analysis, policy violation enforcement), coordinando la prioritizzazione dei finding per CVSS score con i team di sviluppo e garantendo la tracciabilità di ogni finding dal rilevamento alla chiusura. Implementare e mantenere dashboard di monitoraggio continuo della postura di sicurezza dei prodotti (vulnerability density, trending CVE, compliance rate, SLA di remediation), definendo soglie di alert e procedure di escalation verso Product Management. Gestire e presidiare la toolchain DevSecOps condivisa (GitLab CI, SonarQube, Dependency-Track, Nexus, Trivy, Greenbone/GVM), garantendone disponibilità, aggiornamento e corretta integrazione con i repository sorgente. Supportare i team di sviluppo nell’adozione strutturata delle pratiche DevSecOps, fornendo linee guida, template di pipeline riusabili, policy di branching e sessioni di formazione tecnica mirata. Implementare e mantenere meccanismi di gestione sicura dei secret e delle credenziali (Vault, OpenBao o equivalenti), garantendo che nessuna credenziale sia esposta in repository o log di pipeline. Gestire e automatizzare la generazione di SBOM (Software Bill of Materials) per ogni rilascio di prodotto, in supporto alla compliance CRA EU 2024/2847 e ai requisiti contrattuali applicabili. Monitorare le metriche di qualità e sicurezza delle pipeline (copertura dei test, vulnerability density, build success rate, DORA metrics), producendo report di sintesi per CTO e Product Management. Collaborare con le funzioni aziendali per l’integrazione di gate di quality assurance nelle pipeline, garantendo che i criteri di accettazione siano verificati automaticamente prima di ogni release. Gestire l’infrastruttura della piattaforma DevSecOps on-premise in ottica Infrastructure as Code (Ansible/AWX, OpenTofu/Terraform), curando configurazioni, RBAC, backup e ciclo di aggiornamento. Contribuire alla definizione e all’evoluzione del framework DevSecOps aziendale, allineando le pratiche agli standard di riferimento (OWASP DSOMM, OWASP SAMM, CRA EU 2024/2847) e promuovendo il miglioramento continuo della maturità del processo. Titolo di studio : Informatica, Ingegneria Informatica o equivalente Seniority : 3–5 anni di esperienza in ambito DevSecOps, Software Engineering o Platform/Infrastructure Engineering Conoscenze e competenze tecniche: Esperienza nella progettazione e gestione di pipeline CI/CD in ambienti multi-prodotto e multi-team, con approccio pipeline-as-code. Conoscenza delle principali strategie di branching (GitFlow, trunk-based development, release branching) e delle relative policy di merge, protezione dei branch e tagging semantico (SemVer). Esperienza nella composizione e gestione di Software Bill of Materials (SBOM) multi-livello, con tracciabilità delle versioni di tutti i sotto-moduli, librerie e dipendenze di prodotto. Conoscenza approfondita degli strumenti di analisi statica e dinamica del codice (SAST, DAST, SCA) e del loro corretto posizionamento nel ciclo di sviluppo. Capacità di condurre vulnerability assessment su dipendenze software, interpretare CVSS score (v3.1/v4.0) e prioritizzare le attività di remediation in collaborazione con funzioni PSIRT e Quality. Esperienza con tecnologie container (Docker, Kubernetes/OpenShift) e gestione di artifact repository (Nexus, Artifactory). Competenza nella gestione sicura di secret e credenziali (HashiCorp Vault, OpenBao o equivalenti). Capacità di implementare Infrastructure as Code (Ansible/AWX, OpenTofu/Terraform o equivalenti) per la gestione reproducibile degli ambienti. Familiarità con i principi di Shift-Left Security e integrazione della sicurezza nel SDLC (approccio DevSecOps maturity model). Esperienza nello sviluppo di script di automazione (Python, Bash, Groovy) per estensione e personalizzazione delle pipeline. Conoscenza di standard e framework: OWASP DevSecOps Guideline (DSOGL) / OWASP DSOMM (DevSecOps Maturity Model) CRA EU 2024/2847 – requisiti essenziali di cybersecurity per prodotti con elementi digitali (mandatorio da settembre 2026) ISO 29147 / ISO 30111 – vulnerability disclosure e handling process; FIRST.org CVSS v3.1/v4.0 OWASP SAMM o BSIMM – valutazione e miglioramento della maturità dei processi di sicurezza software Competenze comportamentali: Capacità di lavorare in team multidisciplinari, interfacciandosi con sviluppatori, quality manager, responsabili di prodotto e funzioni di compliance. Approccio strutturato, orientato all’automazione, alla riduzione del debito tecnico e all’eliminazione delle attività manuali ripetitive. Attitudine alla continuous improvement e alla condivisione proattiva della conoscenza tecnica con i team di prodotto. Capacità di tradurre requisiti di compliance e sicurezza in vincoli tecnici praticabili e integrabili nel flusso di sviluppo. Conoscenze linguistiche : inglese fluente (documentazione tecnica internazionale e standard di riferimento) Competenze informatiche: GitLab / GitLab CI – pipeline authoring, branching strategy enforcement, protected branches, merge request gates, GitLab Runners Dependency-Track – SBOM ingestion, CVE tracking, policy violation enforcement, prioritizzazione remediation per CVSS score SonarQube, Trivy, OWASP ZAP, Fortify o equivalenti – analisi SAST/DAST/container scanning Greenbone GVM / OpenVAS – vulnerability scanning infrastrutturale e monitoraggio continuo Nexus / Artifactory – artifact repository management, versioning e policy enforcement Docker, Kubernetes / OpenShift – containerizzazione e orchestrazione Ansible / AWX, OpenTofu / Terraform – Infrastructure as Code e configuration management HashiCorp Vault / OpenBao – gestione sicura di secret e credenziali Apache DevLake o strumenti equivalenti – raccolta metriche DORA e qualità di pipeline Python, Bash, Groovy – scripting e automazione Altro (es. Disponibilità a trasferte, Certificazioni specifiche…) : Disponibilità a brevi trasferte per attività di supporto on-site ai team di sviluppo, audit di sicurezza o milestone di prodotto. Certificazioni DevSecOps (es. Certified DevSecOps Professional – CDP, GitLab Certified CI/CD Specialist) costituiscono titolo preferenziale. Coinvolgimento, valorizzazione delle competenze , cura del benessere e della sicurezza delle persone sono i cardini della nostra cultura aziendale. Ci impegniamo ogni giorno a favorire un ambiente di lavoro inclusivo e stimolante, promuovendo attivamente i principi di inclusione, equità e valorizzazione delle diversità . Cosa offriamo? Il nostro contratto collettivo del lavoro di riferimento è il CCNL per Industria Metalmeccanica Privata e della Installazione di Impianti; Modalità di lavoro: Ibrida; Categoria contrattuale: Impiegato; Tipologia contrattuale: tempo indeterminato; Tredicesima mensilità; Premialità legata ai risultati di Business; Buoni Welfare dal valore di 250 euro annui; Mensa aziendale; Opportunità di formazione e aggiornamento continuo delle competenze professionali e delle soft skill; Benessere: mettiamo al primo posto il benessere economico, fisico, sociale e psicologico delle nostre persone, offrendo molteplici soluzioni vicine alle loro esigenze. L’azienda si riserva la possibilità di effettuare valutazioni in merito al livello di inquadramento e alla proposta economica, sulla base di criteri oggettivi emersi nel corso del processo di selezione e in coerenza con la seniority del/della candidato/a individuato/a e della posizione, nel rispetto dei principi di equità, trasparenza e pari opportunità previsti dalla normativa vigente. Aspettiamo la tua candidatura : inviaci il tuo CV entro tre settimane dall’apertura dell’annuncio di lavoro. Come funziona il processo di selezione? A seguito della raccolta delle candidature, vengono valutati e identificati i CV maggiormente in linea con i requisiti richiesti. Le/i candidate/i selezionate/i sostengono un colloquio conoscitivo con il team delle Risorse Umane, motivazionale e attitudinale, seguito da un’intervista di approfondimento tecnico con il Business. Al termine del processo, alla persona viene restituito un feedback, sia in caso di esito positivo che negativo. Seniority: Expert Primary Location: IT - Roma - Via Laurentina Additional Locations: IT - Genova - Fiumara Contract Type: Permanent Total Base Pay Range: 36k - 59k Hybrid Working: Hybrid

Leonardo · Darmstadt - ESOC, Germany

Job Description: MOI-IT System Engineer Description The Mission Operations IT (MOI-IT) infrastructure provides the critical IT services supporting ESA's spacecraft operations, mission preparation activities and ground segment engineering. The infrastructure includes on-premises cloud platforms, virtualisation, Linux systems, container platforms, storage, networking, monitoring and automation services used by multiple ESA missions. As an MOI-IT System Engineer, you will contribute to the design, deployment, operation and continuous evolution of highly available IT platforms supporting mission-critical operations. Working in a multidisciplinary team, you will participate throughout the entire system lifecycle, from requirements engineering and architecture to implementation, validation and operational support. Duties Reporting to the Head of Section, your responsibilities will include: Designing and maintaining mission-critical IT infrastructure supporting ESA spacecraft operations. Engineering Linux-based server platforms and virtual infrastructure. Designing, deploying and operating Kubernetes-based container platforms. Managing enterprise storage solutions, including Ceph and distributed storage technologies. Maintaining databases and associated backup and recovery solutions. Developing Infrastructure-as-Code and configuration management solutions using Ansible and Git. Designing and implementing CI/CD pipelines for automated software deployment. Integrating systems with LDAP/Active Directory identity management services. Implementing secure authentication, certificate lifecycle management and PKI solutions. Supporting mission-specific IT environments during development, validation and operations. Performing system integration, acceptance testing and operational readiness activities. Monitoring system performance, analysing incidents and performing root-cause investigations. Providing second- and third-line engineering support for operational services. Producing High-Level Designs (HLD), Low-Level Designs (LLD), operational procedures and technical documentation. Supporting technology evolution projects and infrastructure modernisation initiatives. Contributing to cybersecurity hardening following ESA security policies and industry best practices. Participating in technical reviews, design reviews and anomaly investigations. Technical Environment The successful candidate will work with technologies such as: Red Hat Enterprise Linux (RHEL) / Ubuntu / SLES Kubernetes Podman / LXD Containers Ceph Storage VMware / KVM virtualisation PostgreSQL / MySQL / MariaDB Git Ansible Jenkins / GitLab CI Python / Bash scripting Prometheus & Grafana LDAP / Active Directory PKI & TLS Certificates NGINX DNS, DHCP, NTP Enterprise Networking SAN/NAS storage Monitoring and logging platforms Required Qualifications Master's degree in Computer Science, Information Technology, Computer Engineering or a related discipline. Several years of professional experience in Linux systems engineering. Experience designing and operating highly available IT infrastructures. Experience with container orchestration technologies, preferably Kubernetes. Experience with automation and Infrastructure-as-Code. Good understanding of networking principles. Experience with enterprise storage technologies. Knowledge of database administration. Experience with scripting using Python or Bash. Familiarity with DevOps practices and CI/CD pipelines. Good analytical and troubleshooting skills. Ability to work in multidisciplinary engineering teams. Excellent communication skills in English. Desirable Experience Experience in one or more of the following areas would be considered an asset: Space mission operations Ground segment engineering High-performance computing Cybersecurity Cloud-native technologies Distributed storage systems Identity and Access Management Disaster Recovery planning Operational monitoring systems Service Management (ITIL) Agile and DevOps methodologies Behavioural Competencies Results Orientation Problem Solving Continuous Improvement Teamwork Customer Focus Innovation Planning and Organisation Technical Excellence What We Offer You will contribute to the IT infrastructure supporting ESA's scientific and operational missions, working with modern technologies in a highly collaborative international environment. The role provides opportunities to influence the evolution of mission-critical infrastructure through automation, cloud-native technologies, cybersecurity and systems engineering while supporting some of Europe's most important space programmes. This profile also aligns well with current MOI-IT activities at ESOC, including Linux platform engineering, Kubernetes, on-premises cloud infrastructure, automation, secure access management, storage, networking, and operational support. Seniority: Senior Primary Location: DE - Darmstadt - ESOC Contract Type: Hybrid Working: Hybrid

Leonardo · Luton - Cap. Green 300, United Kingdom

Job Description: Your Impact As a Principal Software Engineer (DevSecOps), you will play a key role in accelerating the delivery of secure, high-quality software across Leonardo's defence and security programmes. You will help shape and evolve our enterprise DevSecOps capability, enabling teams to deliver features and updates rapidly, reliably and securely. Working within our software engineering community, you will champion modern engineering practices, drive automation, and embed security throughout the software development lifecycle. Through your technical leadership and mentoring, you will help build a collaborative DevSecOps culture focused on innovation, continuous improvement and operational excellence. What You'll Do Contribute to the delivery and evolution of Leonardo's enterprise-wide DevSecOps platform. Support and mentor teams adopting DevSecOps practices, tools and ways of working. Contribute to the planning and implementation of DevSecOps capabilities across cloud, on-premises and hybrid environments. Design, deploy and maintain development, test and operational environments. Drive automation across software delivery and infrastructure provisioning to improve quality, consistency and efficiency. Develop and maintain automation frameworks, CI/CD pipelines and deployment processes. Apply effective change, configuration and release management practices. Support deployed services, ensuring high levels of performance, security and availability. Collaborate with engineers, platform teams and stakeholders to improve delivery capability and engineering practices. Champion secure-by-design principles across the software development lifecycle. What You'll Bring You will have a degree in Computer Science, Software Engineering, Systems Engineering, or a related discipline, together with experience delivering software solutions within a complex engineering environment. We are looking for candidates who can demonstrate: Experience designing, building and operating secure-by-design environments. Hands-on experience with Continuous Integration and Continuous Delivery (CI/CD) practices and tooling. Knowledge of cloud, on-premises and hybrid environments, including associated security considerations. Experience with enterprise DevOps and DevSecOps tools supporting modern software delivery. A background in software engineering, platform engineering, IT operations or a related discipline. Experience with requirements management, configuration management and version control tools. Knowledge of infrastructure-as-code, automation and deployment technologies. Experience working within Agile development environments. Strong communication skills with the ability to mentor and influence technical teams. A passion for automation, continuous improvement and engineering excellence. For a full list of our company benefits please visit our website. Security Clearance This role is subject to pre-employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). An additional range of Personnel Security Controls referred to as National Security Vetting (NSV) may apply, this could include meeting the eligibility requirements for The Security Check (SC) or Developed Vetting (DV). For more information and guidance please visit: https://careers.uk.leonardo.com/gb/en/security-and-vetting Leonardo UK operates a grade-based salary framework with broad bands. The salary range shown reflects the approved grade band for this role, or a narrower hiring range published within that band, and is benchmarked against the external market. Exceptions above the standard range are managed through governance controls to protect internal equity. Leonardo is a global leader in Aerospace, Defence, and Security. Headquartered in Italy, we employ over 53,000 people worldwide including 8,500 across 9 sites in the UK. Our employees are not just part of a team—they are key contributors to shaping innovation, advancing technology, and enhancing global safety. At Leonardo we are committed to building an inclusive, accessible, and welcoming workplace. We believe that a diverse workforce sparks creativity, drives innovation, and leads to better outcomes for our people and our customers. If you have any accessibility requirements to support you during the recruitment process, just let us know. Be part of something bigger - apply now! Primary Location: GB - Luton - Cap. Green 300 Additional Locations: GB - Basildon, GB - Edinburgh, GB - Lincoln, GB - Newcastle, GB - Southampton Contract Type: Permanent Hybrid Working: Hybrid

Docebo · Biassono, Italy

Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. The Senior Cloud Engineer II is responsible for managing and improving the cloud infrastructure that supports Docebo’s applications. This role focuses on maintaining a highly available, scalable, and secure infrastructure using modern approaches, such as DevOps and Platform Engineering. The engineer will work closely with development and engineering teams to release new services, implement automation, and evolve the infrastructure to meet market standards. The role involves leading infrastructure projects and optimizing cloud systems in alignment with business objectives. Primary responsibilities, including but not limited to: The responsibilities listed in this section are representative and not exhaustive. Additional duties may be assigned as needed. - Manage and develop the cloud infrastructure to ensure high availability and reliability. - Improve the security standards of Docebo’s cloud infrastructure, ensuring compliance with industry best practices. - Implement automation solutions to enable infrastructure scalability and reduce manual processes. - Lead and contribute to infrastructure projects, ensuring timely delivery and alignment with business goals. - Collaborate with development and engineering teams to support new service releases and ensure smooth integration with the cloud environment. - Monitor system performance using tools like Datadog to ensure infrastructure stability and provide actionable insights. - Debug and troubleshoot issues within the cloud environment to maintain optimal system health. - Stay updated on market trends and evolve the infrastructure to remain current with best practices.   What it takes to be successful: To be successful as a Senior Cloud Engineer II, you should have strong problem-solving skills, attention to detail, and a proactive approach to improving infrastructure performance. The ability to collaborate with cross-functional teams, especially development and engineering, is critical. A background in cloud services, automation, and infrastructure management is essential. A Bachelor’s degree in Computer Science or a related field can lay the groundwork for success in this role.   Education and Experience: - Advanced experience with Infrastructure as Code technologies for managing complex infrastructure. - Strong expertise in AWS cloud services. - Experience with Docker and Linux-based systems. - Proven experience with Kubernetes (K8S) or Amazon Elastic Kubernetes Service (EKS). - Familiarity with monitoring tools such as Datadog. - Proven experience with Git and GitLab for automations and code management. - Familiarity with DevOps methodologies. - Experience with scripting languages like Python, Bash, or Go (preferred). OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing.   OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul.   OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Fuel for Your Day: Receive a meal voucher for every working day, so you can focus on doing your best work while enjoying a meal that keeps you energized. - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long.

NeN · San Francisco, United States

Infrastructure Engineer — Nen Be one of the founding engineers at Nen, building the platform that powers AI-driven automation across enterprise desktop environments at scale. The Role Architect and scale the infrastructure that provisions isolated desktop containers on demand, globally - Build systems that go from 1000s → millions of automated desktop sessions - Infrastructure-as-code, CI/CD, and SRE practices from day one - Optimize container orchestration for cold start latency and cost efficiency - Security and network isolation as first principles - Own the full cloud stack and lay the groundwork for multi-cloud Requirements - Deep cloud infrastructure expertise — container orchestration, networking, IAM, and beyond - Proven track record running containerized workloads in production at scale - Hands-on with Terraform, Docker, and modern DevOps tooling - Comfortable debugging at the Linux/kernel level (networking, capabilities, process supervision) - Familiarity with AI/ML infrastructure is a strong plus