Principal Application Developer

Description

The Principal Application Developer is the highest-level individual contributor in the Application Development career family and serves as a technical authority across applications, products, and development teams. The role establishes architecture direction, reusable engineering patterns, and practical governance for secure, scalable, maintainable software. The Principal Application Developer defines how approved AI-assisted development strengthens delivery while preserving software quality, traceability, security, privacy, and human accountability.

• Establish technical direction and reference architectures for major applications, shared services, integrations, and modernization initiatives.
• Lead architectural decisions involving application structure, APIs, data, cloud services, integration, security, scalability, reliability, and operational support.
• Define and maintain architecture standards, approved design patterns, technical roadmaps, and development frameworks.
• Evaluate and approve technical designs for high-complexity projects and cross-product initiatives.
• Balance feature delivery, modernization, technical debt, security, reliability, performance, maintainability, and operational priorities.
• Define standards for requirements traceability, technical design, implementation, automated testing, technical documentation, and production readiness.
• Lead architecture reviews, resolve complex technical disagreements, and communicate decisions and tradeoffs to technical and business leaders.
• Identify systemic technical risk and lead or sponsor high-impact remediation, incident investigation, and recovery efforts.
• Research and evaluate emerging technologies, frameworks, platforms, and engineering practices and recommend adoption, limits, pilots, or rejection.
• Mentor Application Developers and Senior Application Developers and develop technical leadership capability across the team.
• Collaborate with IT leadership, product and business leaders, security, infrastructure, privacy, legal, compliance, and other stakeholders on technology strategy and risk.
• Influence technical direction across teams without relying on direct supervisory authority.

• Define approved patterns and guardrails for AI-assisted requirements, design, coding, testing, documentation, technical review, and knowledge use.
• Establish human review and approval points for AI-generated engineering artifacts based on solution risk, data sensitivity, business impact, and practical reviewability.
• Evaluate AI development tools, coding agents, models, integrations, and context sources for business value, architecture fit, security, privacy, interoperability, maintainability, and operational risk.
• Define how trusted business rules, technical standards, repository context, and architecture information may be presented to approved AI systems.
• Establish reusable instructions, reference implementations, validation controls, traceability expectations, and quality measures for AI-assisted delivery.
• Identify risks involving incorrect business logic, insecure code, unsupported assumptions, intellectual property, inadequate testing, sensitive data, or excessive automation.
• Determine when AI is appropriate, when traditional engineering methods should be used, and when an AI-assisted approach should be limited or stopped.
• Promote incremental, reviewable, testable AI-assisted delivery and ensure authorized employees retain final ownership of designs, code, releases, and decisions.

• Expert knowledge of enterprise application architecture, software engineering, integration, security, testing, Dev Ops, operational reliability, and technical-debt management.
• Extensive experience with Microsoft application technologies, including .NET, C#, SQL Server, APIs, cloud services, and modern web-development practices.
• Demonstrated experience setting technical direction, architecture standards, and governance across multiple applications, products, or teams.
• Proven experience leading architectural decisions, modernization efforts, complex technical investigations, and long-term roadmaps.
• Ability to evaluate technical risk, make decisions with incomplete information, and communicate tradeoffs to senior technical and business leaders.
• Demonstrated ability to influence across teams and develop other technical leaders without direct supervisory authority.
• Demonstrated expertise designing, evaluating, or governing AI-augmented…