Principal Engineer, Technology Transformation & AI Enablement

Role overview Provide senior technical leadership for modernization, engineering enablement, and responsible AI adoption across a large enterprise technology portfolio. The role turns broad technology strategy into practical roadmaps, architecture patterns, standards, and guidance that teams can use across applications and platforms. It partners with engineering, architecture, product, security, infrastructure, and delivery leaders to improve how systems are built and operated.

Responsibilities - Advise technical and business leaders and help align architecture decisions with enterprise technology direction. - Assess application and platform landscapes, define future-state architectures, and develop modernization roadmaps. - Guide teams through cloud adoption, platform evolution, technical debt reduction, and complex transformation work. - Establish reusable reference architectures, engineering standards, and implementation patterns; participate in design reviews and governance. - Promote secure, resilient, observable, maintainable software and effective delivery practices, including cloud-native and DevSecOps approaches. - Identify responsible AI use cases and guide adoption through appropriate evaluation, governance, and operational controls.

Requirements - Deep software engineering and architecture experience, including leadership of large-scale modernization or cloud transformation. - Ability to influence technical direction across multiple teams and translate strategy into actionable engineering work. - Experience developing technology standards, governance approaches, reusable patterns, or engineering enablement programs. - Strong understanding of modern architecture and delivery practices, such as distributed systems, APIs, microservices, cloud-native platforms, or DevSecOps. - Experience assessing emerging AI capabilities and addressing responsible, scalable adoption. - Bachelor’s degree in a relevant technical field or equivalent practical experience.

Nice to have - A relevant master’s degree, or certifications in cloud, architecture, Kubernetes, DevOps, security, or AI. - Experience with generative AI, retrieval-augmented generation, agent workflows, model evaluation, guardrails, or human review controls. - Familiarity with architecture decision records, domain-driven design, event-driven systems, or internal engineering platforms.

Benefits and work setup - Remote from anywhere in the continental United States. - Full-time role with medical, dental, vision, paid time off, retirement savings, wellness programs, and eligibility for incentive and equity programs.