AI Data Architect; Remote

Experience Required
:
Minimum 5+ years in data architecture, with recent experience in AI/ML systems

About the Role
:

Radar Hire is seeking a highly experienced and forward-thinking AI Data Architect to design and manage the foundational data infrastructure that powers AI, machine learning, and analytics initiatives for our clients. This is a strategic, hands‑on role responsible for creating scalable data pipelines, optimizing data structures, and enabling real‑time, intelligent decision‑making across enterprise environments.

You’ll work closely with AI engineers, data scientists, software developers, and business stakeholders to architect end‑to‑end data solutions—ensuring data is clean, accessible, secure, and actionable for advanced AI use cases.

• Design and implement scalable, secure, and high‑performance data architectures for AI/ML models and systems
• Build and optimize ETL/ELT pipelines that support real‑time and batch data processing
• Define and enforce best practices for data modeling, schema design, and metadata management
• Collaborate with AI engineers and data scientists to ensure data pipelines support model training, inference, and retraining workflows
• Architect and manage data lakes, warehouses, and cloud‑based storage solutions (e.g., AWS, GCP, Azure)
• Ensure data governance, compliance, and security policies are met (including HIPAA, GDPR, or SOC2, if applicable)
• Monitor data quality and establish automated validation and anomaly detection processes
• Create technical documentation, architecture diagrams, and data flow mappings for internal and external teams
• Evaluate and integrate new tools, frameworks, and platforms to enhance data infrastructure capabilities

• 5+ years in data architecture, data engineering, or a related field
• Strong understanding of AI/ML systems and how they interface with structured and unstructured data
• Expertise with cloud platforms such as AWS (e.g., S3, Redshift, Glue), GCP (Big Query), or Azure
• Proficient in Python, SQL
  , and modern data frameworks (e.g., Apache Spark, Kafka, Airflow)
• Deep experience with relational and No
  
  SQL databases (e.g., Postgre
  
  SQL, Mongo
  
  DB, Dynamo
  
  DB)
• Experience architecting solutions that feed into or support AI models (e.g., LLMs, recommendation systems, predictive analytics)
• Familiarity with MLOps, model lifecycle, and data versioning tools
• Strong documentation, diagramming, and cross‑functional communication skills
• Security‑first mindset with experience implementing data privacy and governance protocols

• Experience supporting LLM‑based AI pipelines or Retrieval‑Augmented Generation (RAG) architectures
• Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and embeddings
• Knowledge of Kubernetes, Docker, or cloud‑native orchestration systems
• Certifications in cloud architecture, data engineering, or AI/ML (AWS Certified Data Analytics, GCP Data Engineer, etc.)

Aligned with U.S. business hours

• Direct access to results‑driven, growth‑oriented entrepreneurs
• Clear expectations and goals with opportunity to make an immediate impact
• Work with autonomy and be a key player in scaling a business

• Competitive compensation tailored to experience and technical depth
• Remote‑first flexibility with global collaboration opportunities
• Work on cutting‑edge AI infrastructure projects across industries
• Opportunities to lead architecture decisions in high‑impact environments
• Collaborative, fast‑paced culture that values innovation and execution