- Lead architectural direction: Take the strategic lead on the architectural direction of impactful enterprise-scale projects across cloud data and AI domains.
- Shape technology decisions: Gain a strategic seat at the table influencing technology decisions that directly impact business outcomes and drive digital transformation efforts.
- Hands-on with cutting-edge tech: Get hands-on experience with cutting-edge technologies including Azure .NET/C# AI integrations and modern data platforms.
- Collaborate and innovate: Work in a collaborative environment alongside cross-functional teams to design robust scalable and secure systems while continuously learning through exposure to emerging tools and architectural patterns.
- Influence and mentor: Define governance standards shape long-term technical roadmaps for cloud-native and hybrid systems and influence engineering best practices mentoring technical talent across multiple teams.
- Build industry expertise: Access high-level technical and business discussions with top-tier clients and partners significantly building your expertise and industry profile.
Requirements
- A bachelor s or master s degree in Computer Science Engineering or a related discipline; certifications in Azure architecture are a plus.
- A minimum of 10 years of experience in software engineering.
- Proven expertise in designing and implementing distributed systems using .NET/C# and Microsoft technologies.
- Deep knowledge of cloud computing concepts.
- Experience designing solutions that integrate with AI/ML components and modern data platforms (e.g. Azure Data Factory or Databricks).
- Strong understanding of microservices event-driven architecture DevOps practices and CI/CD pipelines.
- Excellent communication leadership and stakeholder management skills.
- Ability to balance hands-on engineering with strategic decision-making.
Proven expertise in designing and implementing distributed systems using .NET/C# and Microsoft technologies. Deep knowledge of cloud computing concepts. Experience designing solutions that integrate with AI/ML components and modern data platforms (e.g., Azure Data Factory or Databricks). Strong understanding of microservices, event-driven architecture, DevOps practices, and CI/CD pipelines. Excellent communication, leadership, and stakeholder management skills. Ability to balance hands-on engineering with strategic decision-making.