[Remote] AI Data Engineer

Note: The job is a remote job and is open to candidates in USA. Ranger Technical Resources is a growing SaaS organization in the legal and professional services industry, and they are seeking a Senior AI Data Engineer to help architect and scale their first centralized AI-ready data platform. This highly hands-on role involves building scalable lakehouse infrastructure, developing data models, creating ingestion pipelines, and designing AI workflows to enhance product experiences.

Responsibilities

• Architect and expand a centralized AWS lakehouse platform
• Develop scalable Bronze, Silver, and Gold data models using dbt
• Build ingestion and CDC pipelines across SQL Server and SaaS platforms
• Design and maintain orchestration workflows using Airflow/MWAA
• Support Redshift, Athena, Glue, S3, and Iceberg-based analytics infrastructure
• Build embedding, retrieval, and vector search pipelines for structured and unstructured data
• Design RAG workflows that support AI-powered product experiences
• Implement governance, IAM, encryption, and tenant isolation best practices
• Improve observability, reliability, and scalability across data systems
• Partner with engineering and product leadership on AI platform strategy and architecture
• Help establish engineering standards and best practices within a growing AI ecosystem
• Contribute to future AI agents and MCP-style integrations

Skills

• BS in Computer Science, Information Technology, Engineering, or equivalent experience/field
• Hands-on experience building AWS-based data platforms in production environments
• Proven experience with dbt, SQL, and Python in modern lakehouse or analytics ecosystems
• Experience designing scalable data ingestion and CDC pipelines
• Exposure to production GenAI or RAG implementations
• Background working within SaaS, legal tech, fintech, or regulated environments is highly preferred
• AWS
• Dbt
• SQL
• Python
• Airflow
• MWAA
• Redshift
• Athena
• Glue
• S3
• CDC
• Iceberg
• RAG
• LangChain
• OpenSearch
• Embeddings
• Vector Databases
• Data Modeling
• Multi-tenant SaaS
• Lakehouse Architecture
• Background working within SaaS, legal tech, fintech, or regulated environments is highly preferred

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