Sr. Director - AI Architecture

AI Architecture Leadership

• Lead a team of AI architects responsible for designing end-to-end AI solution architectures across business domains.

• Define and evolve enterprise AI architecture frameworks, patterns, and standards that ensure scalability, interoperability, and performance.

• Drive alignment across Data Science, MLOps, Cloud, and Software Engineering teams to ensure cohesive design and delivery.

• Build reference architectures for reusable AI components (e.g., model pipelines, feature stores, inference APIs, monitoring frameworks).

Strategy and Governance

• Develop the enterprise AI architecture roadmap in partnership with senior IT, product, and business stakeholders.

• Establish architectural governance for AI model lifecycle management from experimentation to production and retraining.

• Ensure AI systems adhere to standards for security, compliance, data privacy, and responsible AI.

• Evaluate emerging technologies (LLMs, generative AI, edge AI, vector databases, knowledge graphs, etc.) for enterprise readiness.

Solution Design and Delivery

• Oversee the design of AI systems that integrate with enterprise data platforms, IoT systems, MES/ERP systems, and industrial automation solutions.

• Ensure AI solutions are modular, configurable, and reusable across business units and geographies.

• Support large-scale AI deployments leveraging cloud-native architectures, containerization, orchestration, and APIs.

• Drive adoption of CI/CD for ML (MLOps), data versioning, and observability practices across teams.

Team and Stakeholder Leadership

• Lead, mentor, and grow a high-performing team of AI architects and technical leads.

• Partner closely with data scientists, software engineers, enterprise architects, and business leaders to translate needs into scalable solutions.

• Communicate complex technical concepts to executive audiences, influencing investment and adoption strategies.

What youll bring (Basic Qualifications)

• 12+ years of experience in software, data, or AI solution architecture; 5+ years in AI/ML systems leadership, or equivalent experience/knowledge.

• Proven experience architecting and scaling AI platforms in an enterprise or industrial context.

• Deep understanding of modern AI/ML technology stacks including MLOps, data pipelines, distributed computing, and model serving.

• Strong background in cloud platforms (Azure, AWS, or GCP) and containerized architectures (Kubernetes, Docker).

• Familiarity with enterprise integration patterns (APIs, messaging, data fabrics) and security practices.

• Ability to operate at both strategic and technical levels defining vision and leading detailed design.

What will make you stand out

• Experience with industrial or manufacturing data systems (SCADA, historians, IoT platforms).

• Knowledge of GenAI technologies (LLMs, embeddings, RAG pipelines) and their operationalization.

• Prior experience establishing architectural governance or CoE structures for AI.

• Advanced degree in Computer Science, Engineering, or a related field.