Principal AI-Native Engineer
appliedis · US Corporate Headquarters - Reston ·
- Seniority
- Principal
- Category
- Software engineering
- Experience
- 12+ years
- Salary
- USD 195,000 – 210,000 / year
appliedis · US Corporate Headquarters - Reston ·
Principal AI-Native Engineer designs and delivers scalable enterprise AI solutions, sets engineering standards, and mentors teams using AI-assisted tools and cloud-native practices.
When you join AIS, you’re joining a mission-driven team that’s passionate about making a difference. You’ll work on projects that matter, alongside industry-leading experts, in an environment that fosters innovation, driving client success, and empowering our team to make a lasting impact. As an employee-owned company, we value collaboration, inclusivity, continuous growth, and shared success.
Employee Ownership: Your contributions directly impact the company’s success, and you share in its achievements.
Continuous Learning: Access to resources, training, and mentorship to support your professional growth.
Inclusive Culture: A workplace where diversity is celebrated, and everyone’s voice is valued.
Mission-Driven Work: Engage in projects that make a meaningful difference for our clients and communities.
At AIS, we're looking for more than just skills - we're looking for driven individuals who are passionate about making a difference, eager to grow, and aligned with our core principles.
Core Knowledge & Skills: Operates as a multi-domain subject matter expert (e.g., Security, Data) with industry depth, defines enterprise patterns, and guides adoption across solutions.
Work & Complexity: Plans and directs the most complex, cross-functional, mission-critical initiatives, and evaluates industry standards to drive innovation and intellectual property.
Quality & Independence: Acts independently with organization-wide influence, sets visionary bars for quality, reliability, and delivery practices.
Teamwork & Communication: Models company values, mentors across the organization, builds formal networks with decision makers, and serves as an external spokesperson.
Consulting & Engagement: Advises executives on strategy, steers long-range planning and new lines of business, and delivers thought-leading presentations at the highest technical level.
The Principal AI-Native Engineer serves as the organization's highest-level hands-on engineering leader for AI-enabled software delivery. This role combines deep expertise in software architecture, cloud engineering, AI-native development practices, platform engineering, and technical leadership. The individual will design and deliver scalable enterprise solutions, establish AI-first engineering standards, mentor engineering teams, and drive adoption of modern Azure and GitHub development ecosystems. The role requires a unique blend of visionary thinking and hands-on execution, with accountability for delivering secure, observable, testable, and maintainable solutions throughout the software lifecycle.
Technical Leadership
Lead the architecture, design, and implementation of complex software solutions.
Translate business requirements into scalable technical specifications and solution designs.
Drive engineering practices across development, testing, deployment, observability, and operations.
Provide technical leadership for engineering teams and serve as a trusted advisor for solution strategy and delivery.
AI-Native Software Engineering
Leverage AI-assisted development tools and AI-native engineering methodologies to accelerate software delivery.
Define and implement effective guardrails, review mechanisms, and quality controls for AI-generated code.
Establish engineering workflows that maximize developer productivity through intelligent automation.
Evaluate emerging AI engineering capabilities and continuously evolve development practices.
Software Design Excellence
Design maintainable, extensible, and resilient systems with long-term sustainability in mind.
Apply test-driven and quality-driven engineering methodologies.
Ensure solutions are secure, observable, scalable, and operationally efficient.
Make architecture and design decisions based on product lifecycle thinking and operational outcomes.
Engineering Quality & Verification
Lead code review practices and engineering quality initiatives.
Define and implement comprehensive testing strategies, including automated testing and acceptance testing methodologies.
Establish standards for deployment validation, monitoring, and production readiness.
Promote engineering accountability throughout the software lifecycle.
Platform & Technology Enablement
Drive adoption of modern development and cloud platforms.
Guide teams in leveraging GitHub, CI/CD pipelines, automation frameworks, and cloud engineering capabilities.
Collaborate with platform teams to optimize developer experience, security, governance, and operational efficiency.
Support integration of AI platforms and services into enterprise software development workflows.
Talent Development & Mentorship
Mentor engineers, technical leads, and architects on engineering design principles and AI-native development practices.
Coach teams on effective system design, testing strategies, and software craftsmanship.
Foster a culture of continuous learning, experimentation, and technical excellence.
Help identify and develop future technical leaders within the organization.
Experience
12+ years of professional software engineering experience.
Proven experience designing and delivering enterprise-scale applications.
Demonstrated ownership of software products throughout their lifecycle, including ongoing operational responsibility.
Extensive experience leading engineering teams and technical initiatives.
Technical Expertise
Strong expertise in software architecture and system design.
Deep understanding of modern software development methodologies and engineering practices.
Experience implementing automated testing strategies and quality engineering practices.
Expertise in code reviews, engineering governance, and technical standards.
Strong understanding of cloud-native architectures and modern software delivery platforms.
AI Engineering Capabilities
Experience utilizing AI-assisted development tools in production environments.
Understanding of AI-native software delivery approaches and engineering workflows.
Ability to establish effective engineering processes that incorporate AI while maintaining quality and security.
Passion for exploring and adopting emerging AI-driven engineering innovations.
Platform & Cloud Knowledge
Experience with cloud platforms and modern application architectures.
Knowledge of source control, CI/CD, infrastructure automation, and deployment pipelines.
Familiarity with platform engineering concepts, security controls, observability, and operational excellence.
Experience working within product-oriented engineering organizations.
Experience owning software products or platforms through multiple release cycles.
Strong understanding of software operational models and production support practices.
Experience delivering highly scalable distributed systems.
Knowledge of enterprise security, governance, and compliance requirements.
Experience implementing developer productivity platforms and engineering enablement initiatives.
Applied Information Sciences does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis. Employment decisions are based solely on qualifications, merit, and business needs.