Principal AI-Native Engineer

Applied Information Sciences•Reston, VA

About The Position

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. At AIS, we are dedicated to providing our employees with diverse opportunities to grow their careers while supporting a variety of impactful projects. For this position, we are seeking a talented individual to join AIS as a Senior Software Architect. As your initial project assignment, you will support the unique needs of our client as a Principal AI-Native Engineer. 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.

Requirements

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.
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.
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.
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.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.
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.
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.