AI/ML Enterprise Architect

Enterprise AI/ML & Transformation Architect

Location: Remote

Position Overview

Our client is seeking an accomplished Enterprise AI/ML & Transformation Architect to drive enterprise-wide transformation through the design, implementation, and scaling of advanced data, artificial intelligence, and cloud architectures.

This role requires deep expertise across AWS, including Amazon Bedrock, Kafka, AI orchestration, agentic workflows, Retrieval-Augmented Generation (RAG), and enterprise-scale technology modernization . The ideal candidate will architect and scale Machine Learning and Generative AI solutions across complex environments that include both modern cloud platforms and legacy systems.

The Enterprise AI/ML & Transformation Architect will help define future-state architecture, modernize technology ecosystems, guide the adoption of emerging technologies, and ensure solutions deliver scalability, security, regulatory compliance, operational resilience, and measurable business value across a complex, international organization. The environment supports a large, global workforce and diverse lines of business, with technology spanning insurance and claims-related operations, workforce and absence management, customer-facing services, enterprise data platforms, and highly regulated business processes. The role will help connect these business domains through modern AI, data, cloud, and integration architectures while supporting transformation across multiple countries and operating environments.

What you will be doing:

• Define and maintain target enterprise architectures supporting large-scale transformation initiatives, including Machine Learning, Generative AI, agentic systems, AWS/Bedrock, Kafka event streaming, and hybrid legacy environments.
• Design business and technology architectures spanning multiple countries, integrating cloud-native platforms such as AWS and Azure with on-premises and legacy systems.
• Develop reference architectures and standards for enterprise deployment of AI, GenAI, RAG, and agentic workflows, including orchestration and integration best practices.
• Partner with business and technology leaders to identify opportunities to apply AI, automation, analytics, event-driven architecture, and cloud modernization to business processes and customer experiences.
• Evaluate emerging technologies, platforms, and architecture options and recommend future-state solutions based on business value, scalability, cost, security, governance, and regulatory requirements.
• Determine when traditional Machine Learning, Generative AI, RAG, agentic systems, or combinations of these approaches are most appropriate for enterprise use cases.
• Lead architecture governance across transformation programs, ensuring alignment with enterprise strategy and successful modernization of legacy platforms.
• Define architecture roadmaps, capability models, solution blueprints, and multi-year transformation plans.
• Design advanced knowledge management architectures, including vector databases, knowledge graphs, and memory layers to support search, reasoning, and decision-support capabilities.
• Define integration patterns and APIs supporting secure, high-throughput connectivity between AI solutions, agentic workflows, Kafka event streams, AWS/Azure services, data platforms, business applications, document management platforms, and legacy systems.
• Establish and guide LLMOps and AgentOps operating models, including evaluation, observability, monitoring, security, governance, and lifecycle management for AI and agentic solutions.
• Lead the industrialization and scaling of AI solutions from proof of concept through enterprise production deployment.
• Support technical delivery teams throughout implementation, providing architecture guidance and helping resolve integration and deployment challenges across modern and legacy environments.
• Collaborate with Agile delivery teams, Product Owners, technology partners, and other stakeholders to ensure scalable and sustainable implementation of AI and cloud solutions.
• Advise executive stakeholders through architecture recommendations, technical assessments, impact analyses, and strategic insights supporting technology and investment decisions.
• Guide the integration and adoption of emerging technologies, including AWS Bedrock, Kafka, AI orchestration platforms, agentic workflows, and cloud-native capabilities.

Qualifications & Experience

• 10+ years of experience in Enterprise Architecture, AI Architecture, Digital Transformation, Technology Strategy, Technology Consulting, or a related discipline.
• Extensive hands-on experience designing, deploying, and scaling AI, Generative AI, RAG, agentic workflows, AI orchestration, Kafka, and cloud solutions , particularly within complex enterprise environments.
• Strong experience with AWS and Amazon Bedrock , along with experience integrating cloud-native and legacy/on-premises environments.
• Demonstrated experience leading enterprise-wide transformation initiatives involving technology modernization, process transformation, operating model evolution, and organizational change.
• Proven ability to design enterprise-scale application, data, AI, and integration architectures across complex technology ecosystems.
• Experience defining target-state architectures, technology roadmaps, architecture standards, and multi-year transformation strategies.
• Familiarity with LLMOps, AgentOps, AI observability, AI evaluation, and AI lifecycle management .
• Experience with advanced knowledge management architectures, including vector databases, knowledge graphs, and memory layers .
• Strong understanding of event-driven architectures and Kafka or comparable event-streaming technologies.
• Ability to balance innovation and business value with security, governance, regulatory compliance, cost, scalability, and operational resilience .
• Strong communication and stakeholder management skills, with the ability to influence technical and executive audiences.
• Experience working with distributed, international, and multicultural teams.
• Ability to guide technical teams through the implementation and scaling of AI and cloud architectures while maintaining interoperability with existing enterprise systems.

Education & Certifications

• Master’s degree or equivalent in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, or a related discipline preferred.
• Degree from an accredited university, engineering school, or equivalent international program.
• Professional certifications or executive education in AI, Data, Cloud, Enterprise Architecture, or related disciplines are strongly preferred.
• Certifications such as AWS Certified Solutions Architect or Confluent Kafka certifications are a plus.