AI Architect

• Strong expertise across the full Software Development Lifecycle (SDLC).
• Hands-on experience with AI and Generative AI technologies and their application to software delivery.
• Deep understanding of modern software architecture patterns, distributed systems, microservices, and cloud-native solutions.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Strong knowledge of DevOps practices, CI/CD pipelines, infrastructure automation, and platform engineering.
• Experience defining enterprise-wide engineering standards, architecture governance, and best practices.
• Understanding of AI governance, security, compliance, and risk management principles.
• Proven track record of leading large-scale technology transformation initiatives.
• Strong knowledge of application security, data governance, and regulatory compliance requirements.
• Excellent stakeholder management, communication, and leadership skills.
• Fluent English, both written and spoken.

Nice to have:

• Experience with OpenAI technologies.

• Define and drive the enterprise AI engineering strategy, standards, and technology roadmap.
• Establish and maintain architecture principles, engineering best practices, and AI governance frameworks.
• Lead the adoption of AI-native software development practices across the software delivery lifecycle.
• Provide technical leadership and guidance to engineering teams on effective use of AI tools and platforms.
• Design and oversee scalable, secure, and compliant AI-enabled solutions and development processes.
• Ensure software quality, security, traceability, and regulatory compliance in AI-assisted development environments.
• Define standards for AI-supported requirements management, solution design, coding, testing, deployment, and operations.
• Evaluate emerging AI technologies, frameworks, and engineering methodologies to drive innovation and continuous improvement.
• Collaborate with senior stakeholders, architects, product leaders, and delivery teams to align engineering initiatives with business objectives.
• Mentor senior engineers and architects, fostering technical excellence and a culture of innovation.
• Monitor AI adoption, effectiveness, and risk management across engineering organizations.
• Drive enterprise-wide transformation towards AI-driven software delivery and operational excellence.