We are looking for an AI Platform Architect to shape and implement the technical foundation of our enterprise AI ecosystem.
In this role, you will report to the Director of AI Technology in the IT Organization and define the architectural standards and core design principles that enable the secure, scalable, and responsible deployment of AI infrastructure and custom individual use cases across the organization. As a key member of the IT AI technology team, you will lead the integration of enterprise-grade AI platforms with custom-built components for reasoning, retrieval, orchestration, and agentic AI solutions aligned with the wider digital/data environment. Your work will establish the foundation for a composable, extensible AI platform that powers high-impact business use cases across the organization.
Your engagement will be focused on two areas: Deploying a low/no code solution(s) to enable the broader workforce and defining and implementing technical platforms for large use-case development implemented by developers and data scientists with AI expertise.
Responsibilities
Design and maintain a modular, scalable AI architecture to enable the broader workforce to create and deploy their own AI solutions including AI Agents
Develop systems that allow the discovery, usage, and tracing of AI/ML models and agents
Implement budget and usage guardrails using us and cloud security solutions
Lead the design of systems supporting large use-case development including AI/ML Model deployment, maintenance and monitoring
Establish architectural standards for responsible AI, including prompt versioning, access control, monitoring, and explainability
Ensure secure, efficient, and governable interoperability between third-party platforms and internal services, supporting a unified and extensible AI ecosystem
Reporting to the Director of AI Technology you will collaborate with IT and AI Transformation teams to align architectural decisions with business and platform strategy
Serve as a key technical advisor across engineering, security, data, and vendor teams ensuring consistency, scalability, and compliance across the AI stack.
In this role, you will report to the Director of AI Technology in the IT Organization and define the architectural standards and core design principles that enable the secure, scalable, and responsible deployment of AI infrastructure and custom individual use cases across the organization. As a key member of the IT AI technology team, you will lead the integration of enterprise-grade AI platforms with custom-built components for reasoning, retrieval, orchestration, and agentic AI solutions aligned with the wider digital/data environment. Your work will establish the foundation for a composable, extensible AI platform that powers high-impact business use cases across the organization.
Your engagement will be focused on two areas: Deploying a low/no code solution(s) to enable the broader workforce and defining and implementing technical platforms for large use-case development implemented by developers and data scientists with AI expertise.
Responsibilities
Design and maintain a modular, scalable AI architecture to enable the broader workforce to create and deploy their own AI solutions including AI Agents
Develop systems that allow the discovery, usage, and tracing of AI/ML models and agents
Implement budget and usage guardrails using us and cloud security solutions
Lead the design of systems supporting large use-case development including AI/ML Model deployment, maintenance and monitoring
Establish architectural standards for responsible AI, including prompt versioning, access control, monitoring, and explainability
Ensure secure, efficient, and governable interoperability between third-party platforms and internal services, supporting a unified and extensible AI ecosystem
Reporting to the Director of AI Technology you will collaborate with IT and AI Transformation teams to align architectural decisions with business and platform strategy
Serve as a key technical advisor across engineering, security, data, and vendor teams ensuring consistency, scalability, and compliance across the AI stack.
Requirements:
Bachelors Degree and 7+ years of experience in software, AI/ML architecture roles, including experience designing large-scale distributed systems.
Experience with DevOps, CI/CD and orchestration tooling (Ansible, Terraform, Puppet, Jenkins, GitLab, Azure DevOps)
Demonstrated experience designing or integrating AI/ML architectures using third-party platforms (Kubeflow, MLflow, or Azure Machine Learning)
Familiarity with vector database solutions (Pinecone, PGVector)
Experienced with designing or integrating RAG pipelines and retrieval systems grounded in internal enterprise data.
Familiarity with low-code/no-code GenAI platforms (LangFlow, C3.AI, H2O.ai)
Familiarity with at least one major cloud provider (Azure, AWS, or GCP), including identity, security, and observability tools.
Experience implementing access controls, model usage policies, and prompt logging mechanisms for responsible AI deployment.
Strong communication and documentation skills; able to translate technical designs into actionable implementation plans.
Bachelor's or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
Bachelors Degree and 7+ years of experience in software, AI/ML architecture roles, including experience designing large-scale distributed systems.
Experience with DevOps, CI/CD and orchestration tooling (Ansible, Terraform, Puppet, Jenkins, GitLab, Azure DevOps)
Demonstrated experience designing or integrating AI/ML architectures using third-party platforms (Kubeflow, MLflow, or Azure Machine Learning)
Familiarity with vector database solutions (Pinecone, PGVector)
Experienced with designing or integrating RAG pipelines and retrieval systems grounded in internal enterprise data.
Familiarity with low-code/no-code GenAI platforms (LangFlow, C3.AI, H2O.ai)
Familiarity with at least one major cloud provider (Azure, AWS, or GCP), including identity, security, and observability tools.
Experience implementing access controls, model usage policies, and prompt logging mechanisms for responsible AI deployment.
Strong communication and documentation skills; able to translate technical designs into actionable implementation plans.
Bachelor's or Masters degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
This position is open to all candidates.
