IT Director, Data & AI Architecture (AI)

Company

hirify.global is a global healthcare leader developing technologies across diagnostics, medical devices, nutrition, and branded generic medicines, serving people in more than 160 countries.

What you will do

• Define hirify.global's enterprise data and AI architecture vision, target-state architecture, technical standards, and modernization roadmap.
• Lead architecture reviews, challenge solution designs, chair architecture review boards, and advise engineering, architecture, business, and executive stakeholders.
• Design enterprise-scale lakehouse, cloud data platform, integration, DataOps, platform engineering, and Infrastructure as Code architectures.
• Establish standards for data products, data contracts, metadata, lineage, interoperability, Data Mesh, federated ownership, and information architecture.
• Architect AI-ready ecosystems for machine learning, predictive analytics, Generative AI, agentic AI, RAG, semantic search, vector databases, and enterprise AI platforms.
• Define LLMOps, MLOps, governance, observability, privacy, security, data quality, and regulatory controls while maintaining platform scalability, reliability, performance, and cost efficiency.

Requirements

• Master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field.
• 10+ years of experience in enterprise data architecture, cloud data platform architecture, or large-scale analytics architecture, including at least 5 years designing and implementing modern cloud-native data platforms and enterprise-scale architectures.
• 10+ years of overall professional technology experience with a strong background in enterprise architecture and solution design.
• At least 3 years at Director level or in a comparable senior individual contributor leadership role.
• Demonstrated technical architecture leadership, including establishing architectural direction and driving strategic technology initiatives.
• Deep hands-on expertise with Snowflake, Databricks, Microsoft Fabric, Azure Data Services, or equivalent modern data platforms, plus experience designing large-scale lakehouse architectures.
• Experience architecting AI-ready data ecosystems for machine learning, Generative AI, vector retrieval, semantic search, and RAG architectures.
• Strong understanding of Data Mesh, Data Fabric, Data Products, domain-driven design, and modern information architecture principles.
• Experience with enterprise integration patterns, APIs, event-driven architectures, Kafka, streaming platforms, real-time processing, metadata, lineage, master data management, and data quality.
• Experience leading architecture reviews and providing technical oversight for strategic enterprise initiatives, with strong communication and influencing skills across executives, architects, engineers, and business stakeholders.

Nice to have

• Experience as a Chief Data Architect, Lead Data Architect, Enterprise Data Architect, Principal Architect, or similar senior architecture leader.
• Experience in healthcare, medical devices, life sciences, pharmaceuticals, or regulated manufacturing.
• Hands-on experience with Databricks, Snowflake, Microsoft Fabric, Azure, Kubernetes, Apache Airflow, Delta Lake, Apache Iceberg, Kafka, and related cloud-native technologies.
• Experience with vector databases, knowledge graphs, semantic search platforms, and enterprise AI platforms.
• Relevant certifications in Cloud Architecture, Data Engineering, AI Engineering, Enterprise Architecture, or related disciplines.

Culture & Benefits

• Base pay ranges from $149,300.00 to $298,700.00; the range may vary by specific location.
• Serves as a senior hands-on technical leader and trusted advisor rather than a people manager.
• Expected first-year outcomes include establishing the enterprise Data & AI Architecture roadmap, defining modernization standards, and accelerating legacy data environment modernization while maintaining operational stability.
• Success includes increasing adoption of reusable, trusted, scalable data assets and enabling AI, analytics, and automation capabilities supporting business outcomes.