Consultant working on business-critical digital projects, shaping software products and technical solutions across a wide technical spectrum.
Responsibilities
Shape software products and technical solutions for clients
Engage with clients and deliver on projects across fullstack, backend, data science & engineering, cloud, architecture, web development, AI, and DevOps
Define own career path and role based on strengths and market demand
Collaborate with mentors, coaches, and network communities
Lead and coordinate a team of software engineers to bring AI and GenAI solutions into production, manage the product engineering lifecycle, and ensure operational reliability of AI-powered applications.
Responsibilities
Lead and coordinate a team of software engineers
Manage the product engineering lifecycle
Coordinate software releases and deployment schedules
Ensure applications meet code quality, security, performance, and documentation standards
Plan engineering capacity and allocate resources
Requirements
Degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Build and modernize large‑scale build, deployment, and change‑management systems for Apple’s cloud services, integrating AI to automate risk assessment, incident triage, and developer support.
Responsibilities
Design and implement scalable backend services for build and deployment pipelines
Modernize legacy tooling and standardize containerized deployment workflows
Develop agentic AI systems for risk assessment and incident triage
Integrate with microservices, messaging systems, and AI/ML frameworks
Collaborate with cross‑functional engineering teams to improve developer experience
Design, develop, and maintain full stack applications and data solutions, ensuring secure, scalable, and high-performance delivery across backend services, APIs, frontend interfaces, and data pipelines.
Responsibilities
Design, develop, and maintain full stack applications across backend services, APIs, and frontend interfaces.
Build and optimise data pipelines, models, and integration routines across multiple systems.
Perform data analysis, profiling, mapping, and documentation of end-to-end data flows.
Apply secure coding practices, encryption controls, and follow CBA risk and compliance frameworks.
Support CICD, cloud deployments, system monitoring, and performance tuning.
Requirements
Bachelor's degree in Engineering, Computer Science, Information Technology or a related discipline, or equivalent practical experience.
Lead Software Engineer within the Accelerator business focused on building backend services, cloud-native applications, and leading the adoption of AI-assisted engineering practices in fintech.
Responsibilities
Design backend services and interfaces using clear domain models
Build secure, scalable cloud-native services
Structure code for readability, testability, and safe evolution through modular design
Develop automated tests and delivery automation
Investigate incidents and defects, perform root-cause analysis
Progettare e implementare architetture moderne di Big Data & Analytics, gestendo pipeline di dati complesse e guidando tecnicamente team.
Locations (3)
Milano, Lombardy, Italy
Firenze, Tuscany, Italy
Verona, Veneto, Italy
Compensation
RAL indicativa 34.000€ - 40.000€
Responsibilities
Progettare e sviluppare architetture backend e infrastrutture dati scalabili, performanti e sicure
Costruire e gestire pipeline di dati complesse (ETL/ELT) e modelli di integrazione
Promuovere l'evoluzione tecnologica proponendo nuovi pattern architetturali e soluzioni cloud-native
Monitorare e ottimizzare le performance dell'infrastruttura backend
Coordinare tecnicamente le fasi di sviluppo e condividere best practice con le figure junior
Canada
Compensation
The starting salary range posted for this position is $149,100.00 to $218,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Responsibilities
Partner with enterprise customers to understand technical requirements and business goals.
Design scalable AI solution architectures and guide customers through production deployments.
Build integrations, prototypes, and reusable tools that accelerate customer success.
Lead technical workshops, architecture discussions, and troubleshoot complex production issues.
Collaborate with Product and Engineering teams to share customer feedback and influence future product enhancements.
Requirements
Bachelor's in Computer Science
Nice to have: Deploying or supporting Generative AI, LLM, or Machine Learning applications in production
Nice to have: Experience with Kubernetes, cloud infrastructure, observability, or MLOps
Nice to have: Experience building customer-facing technical solutions or integrations
Nice to have: Experience creating reusable developer tools, frameworks, or open-source contributions
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