Enterprise Architect, Agentic AI Implementation

Location: UK (Remote)

Job Overview

A strategic leader responsible for defining and implementing an enterprise-wide architecture for autonomous AI agents and Generative AI solutions. This role requires deep expertise in enterprise architecture, AI systems design, and cloud-native platforms (specifically Microsoft Azure, leveraging services like Azure AI Studio/Foundry, Azure OpenAI, Databricks).

Collaborate with C-suite executives, Directors, Business & technology stakeholders, data scientists, and engineering teams to ensure that AI initiatives are scalable, secure, ethically sound, and aligned with Ecolab's core business of water, hygiene, and infection prevention solutions.

Key Responsibilities

• AI Strategy and Roadmap: Own and develop the enterprise AI architecture strategy and technical roadmap, ensuring alignment with Ecolab's business goals and digital transformation initiatives.
• Architectural Design and Governance: Design end-to-end scalable, secure, and resilient architectures for agentic AI solutions and multi-agent systems, integrating them with core enterprise systems like SAP, Salesforce, and the ECOLAB3D platform. Define and enforce architectural standards and governance frameworks for the agent lifecycle, data lineage, observability, and interoperability.
• Technology Evaluation and Selection: Evaluate and select AI platforms, tools, and protocols, such as LangChain, AutoGen, or similar frameworks, ensuring they meet scalability, security, and performance requirements within the Azure environment.
• Implementation Oversight: Guide development and operations teams through the deployment, integration, and testing of AI solutions. Champion best practices in AIOps, LLMOps, and agile methodologies to ensure smooth delivery and production deployment.
• Data and Integration: Ensure data readiness for AI initiatives, collaborating with data engineers to design robust data pipelines (leveraging tools like Databricks) that provide timely, accurate, and contextual data to AI agents.
• Security, Ethics, and Compliance: Embed robust security measures, data privacy, and ethical AI principles into every architectural layer. Ensure solutions comply with global AI regulations and internal governance policies.
• Stakeholder Collaboration & Change Management: Collaborate with cross-functional teams, including product managers, data scientists, and business leaders, to translate business needs into AI solutions. Lead change management initiatives to foster adoption and ensure human oversight and a clear escalation path for autonomous agents.
• Innovation and Research: Stay current with industry trends and emerging technologies in Generative AI and Agentic AI, introducing novel approaches to enhance the architecture practice and identify new business opportunities.

Qualifications

• 15+ years of IT experience, with at least 5+ years in an enterprise architecture role and 3+ years in AI/ML, including practical experience with Agentic AI systems and Generative AI.
• Deep expertise in enterprise architecture frameworks (e.g., TOGAF, Zachman) and cloud-native architecture (preferably Microsoft Azure).
• Understanding LLMs and Python-based agentic frameworks like LangChain or AutoGen.
• Strong understanding 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.