Principal Systems Engineer - Artificial Intelligence

transformation initiatives across the organization. This is a senior leadership and consulting role responsible for identifying, shaping, and implementing high-value AI use cases that improve operational efficiency, enhance employee experience, optimize service delivery, and accelerate business outcomes.

The successful candidate will work closely with cross-functional and transversal teams across technology, operations, engineering, service management, tooling, and business functions to establish AI as a strategic capability. They will serve as a trusted advisor, thought leader, and hands-on practitioner capable of translating business challenges into scalable AI solutions.

This role requires a combination of strong AI expertise, business consulting skills, stakeholder management, and execution excellence.

AI Strategy & Transformation

• Define and drive the organization's AI vision, roadmap, and transformation strategy.

• Identify opportunities where AI, Generative AI, Agentic AI, Machine Learning, and automation can create measurable business value.

• Develop AI use case portfolios aligned with organizational priorities and strategic objectives.

• Establish frameworks to prioritize AI initiatives based on value, feasibility, risk, and business impact.

• Act as a trusted advisor to leadership teams on AI adoption and innovation opportunities.

Business Consulting & Innovation

• Partner with business and technology stakeholders to understand challenges and identify AI-driven solutions.

• Facilitate ideation workshops and design-thinking sessions to generate innovative use cases.

• Translate business requirements into AI solution architectures and implementation plans.

• Build compelling business cases, value realization models, and executive presentations.

• Champion AI adoption and help drive organizational change.

Solution Design & Implementation

• Lead end-to-end delivery of AI initiatives from concept through production deployment.

• Design and implement solutions leveraging:

  • Generative AI
  • Large Language Models (LLMs)
  • Agentic AI
  • Machine Learning
  • Conversational AI
  • Predictive Analytics
  • Intelligent Automation

• Collaborate with enterprise architecture, engineering, security, and operations teams to ensure scalable and secure implementations.

• Establish best practices for AI architecture, governance, monitoring, and lifecycle management.

Cross-Functional Collaboration

• Work closely with transversal teams across multiple functions and geographies.

• Build strong relationships with business leaders, technical teams, and external partners.

• Influence stakeholders at all levels to drive AI adoption and transformation.

• Act as the bridge between business strategy and technical execution.

AI Governance & Responsible AI

• Establish governance frameworks ensuring ethical, secure, compliant, and responsible AI usage.

• Define standards for model governance, risk management, explainability, and data privacy.

• Ensure adherence to organizational, customer, and regulatory requirements.

• Promote responsible AI principles throughout the organization.

Capability Building

• Create and drive AI awareness programs, communities of practice, and training initiatives.

• Mentor teams on AI concepts, methodologies, and best practices.

• Foster a culture of innovation and experimentation.

• Stay current on emerging AI trends, technologies, and industry best practices.