.NET Fullstack Development

Roles & Responsibilities:

Scope

Collaborate with cross-functional teams to prepare technical design specifications based on product management and architectural initiatives

Drive Architectural Governance activities

Seek platform convergence

Plan across engineering initiatives and new feature delivery to find a balance between customer delivery and organizational health

Identify opportunities for improvement in applications and provide actionable recommendations to the teams

Assist and mentor development staff in the delivery of product features

Excellence

Helping to build successful teams that have a learning culture by providing direction and fostering communication to help teams make decisions to accomplish their goals

Assisting teams with technical conversations, driving towards action and a successful outcome

Communication & Influence

Build strong relationships with your team and stakeholders

Care about our customers and the impact our software has on their business outcomes

Demonstrate a willingness to learn, adjusting as needed to make improvements to the team s processes, etc.

Provide feedback to peers and teams to instill a learning culture

Communicating clearly with executive leadership, peers, and development teams

Favor optimism

Professional & Technical Skills:

Significant experience in design (architecture, design patterns, reliability, and scaling) and implementation or enhancement of new and current systems.

Significant experience in system engineering involving analytical systems design and implementation.

Fluency and specialization with modern languages such as Java, C# or Python

Experience in building products using microservices architectural patterns and extensible REST APIs.

Experience in design (architecture, design patterns, reliability, and scaling) and implementation or enhancement of new and current systems.

Familiarity with continuous delivery and infrastructure as code.

Proven experience leading cloud, DevOps, or AI modernization initiatives.

Strong understanding of LLMs, automation, and engineering toolchains.

Ability to translate AI innovation into business and productivity impact.