IT Infrastructure Leader (R&D Data & AI Platform)

Position: IT Infrastructure Leader - R&D Data & AI Platform Location: Hybrid in Atlanta, GA preferred Conversion Salary: $150,000-$200,000. Exact compensation may vary based on several factors, including skills, experience, and education. The IT Infrastructure Leader for the R&D Data & AI Platform is responsible for designing, building, and operating the technical backbone of the organization’s R&D digital transformation. This means unifying fragmented laboratory and factory data systems into a coherent, AI-ready data platform, and engineering the infrastructure that powers the R&D AI copilot, knowledge graph, and predictive analytics capabilities. This role sits at the intersection of enterprise IT, cutting-edge AI engineering and R&D Materials organizations. Required Qualifications: • Bachelor's degree or higher in Computer Science, Software Engineering, Data Engineering, or a related field. • Minimum 8 years of experience in data engineering, platform engineering, or enterprise IT architecture. • Demonstrated experience designing and operating cloud data platforms (Databricks, Snowflake, Azure Synapse, AWS Glue, or equivalent). • Hands-on experience with LLM integration, vector databases (e.g. Pinecone, Weaviate, pgvector), and RAG architecture. • Experience integrating with laboratory informatics or enterprise systems in a scientific or regulated environment is strongly preferred. • Proven ability to lead technical teams and manage delivery across complex, multi-vendor environments. Preferred Qualifications: • Experience in pharma, chemical, battery, or materials R&D IT environments. • Familiarity with knowledge graph technologies (Neo4j, RDF/SPARQL, or property graph databases). • Exposure to scientific data standards (FAIR data principles, ISA framework, or equivalent). • Certifications in cloud architecture (AWS Solutions Architect, Azure Solutions Architect, or GCP Professional Data Engineer). Competencies: • Technical depth with breadth — deep in data engineering and AI infrastructure, fluent across adjacent domains (security, MLOps, enterprise integration). • Scientific empathy — able to understand R&D workflows and translate them into platform requirements without needing to be a scientist. • Pragmatic delivery — ships working systems incrementally; avoids over-engineering while maintaining long-term architectural integrity. • Vendor & stakeholder management — navigates complex vendor relationships and communicates technical tradeoffs to non-technical leaders. • Security mindset — treats IP protection and data governance as first-class concerns, not afterthoughts. Compensation: $150,000 to $200,000 per year annual salary. Exact compensation may vary based on several factors, including skills, experience, and education.