Enterprise Architect

Key responsibilities:

• Define and own the enterprise AI architecture strategy and technical roadmap aligned with business goals.
• Design secure, scalable AI architectures and set governance standards for agent life cycle, data lineage, and interoperability.
• Assess and select AI platforms and frameworks (eg, LangChain, AutoGen) for performance and security within Azure.
• Guide teams on deployment, integration, and testing; promote best practices in AIOps, LLMOps, and agile delivery.
• Ensure data readiness by building robust pipelines with tools like Databricks for timely, accurate inputs to AI agents.
• Embed security, privacy, and ethical AI principles; ensure compliance with global regulations and internal policies.
• Work with cross-functional teams to translate business needs into AI solutions and drive adoption.
• Stay ahead of trends in Generative and Agentic AI; introduce new approaches to enhance architecture and unlock opportunities.

Your Profile

Essential skills/knowledge/experience:

• Extensive experience in the IT domain, with strong expertise in an enterprise architecture role and AI/ML, including practical experience with Agentic AI systems and Generative AI.
• Deep expertise in enterprise architecture frameworks (eg, TOGAF, Zachman) and cloud-native architecture, preferably on Microsoft Azure.
• Understanding of LLMs and Python-based agentic frameworks like LangChain or AutoGen.
• Strong knowledge of data governance, security protocols, and MLOps practices in a cloud environment.
• Proven track record of designing and deploying scalable AI solutions that deliver measurable business value.
• Excellent communication, leadership, and analytical skills, with the ability to influence stakeholders at all levels.