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• 7+ years of experience as a software engineer and solution architect, delivering complex, enterprise-grade systems
• Relevant project experience in which you acted as a Product Owner, Product Manager, Scrum Master or Tech Lead.
• Proven track record in shaping and delivering large-scale Engineering, Cloud, AI and Data transformation programmes end-to-end
• Extensive experience advising senior executives and acting as a strategic partner

Accelerate our growth in Engineering and contribute through your strategic vision, commercial drive and deep expertise in Engineering, AI and data-driven transformation. At Deloitte.

• Lead strategic and commercial growth of AI & Data offerings ;
• Identify and shape opportunities, define proposals, and convert them into impactful engagements;
• Pave the way for (our) technology experts and software engineers to start with engagements around platform and product strategy, design and architecture;
• Deliver transformation programmes focused on enterprise data platforms, AI, cloud, and emerging technologies;
• Guide clients in developing Engineering, AI & Data blueprints and roadmaps;
• Manage the full project lifecycle, from early visioning to implementation and adoption;
• Inspire, coach and develop multidisciplinary project teams;
• Foster a learning environment with continuous growth opportunities;
• Partner with Talent teams to attract, develop and retain top talent;
• Champion a high-performance culture based on collaboration and integrity.

• Deep passion for technology, combining broad knowledge with strong depth in key domains
• Able to simplify complex technical topics into clear, actionable insights

In-depth experience with various technology stacks, including:

• Cloud platforms: AWS, Azure, GCP; cloud-native architectures such as microservices, serverless and Kubernetes;
• Data and AI platforms: Databricks, Snowflake, real-time data streaming (e.g., Kafka, Airflow) and MLOps;
• Generative AI and advanced analytics: LLMs, prompt engineering, AI orchestration and responsible AI;
• Integration and APIs: event-driven architecture and API management;
• DevoOps and platform engineering: CI/CD, infrastructure as code and observability;
• On-premise infrastructure and open source tools;
• Networking: CCST / CCNA / CCNP, CCIE, etc.