AI Data Engineer

Quantifind helps major banks combat money laundering and fraud through their AI platform. As an AI Data Engineer, you will drive data prototyping and manage ETL pipelines, ensuring data quality and compliance while working with both structured and unstructured data.

Responsibilities:

• Drive data discovery, open-source intelligence (OSINT) and related data acquisition, and commercial data ingestion
• Build and manage reliable ETL pipelines with a focus on speed from discovery to value, including database indexing, performance tuning, concurrency, and load balancing
• Perform data quality assurance and independent testing
• Work across structured and unstructured data parsing, enrichment, data architecture, ontology management, knowledge graphs, and data fusion
• Manage data compliance, documentation, and data cards

Requirements:

• US Citizen
• 4+ years of professional experience, including graduate or Ph.D. work if relevant
• Technical education
• Forward-leaning in AI coding, with traditional technical training as a foundation
• Hands-on with AI coding tools and agentic workflows (Claude Code, GPT/Codex, Cursor, Windsurf), including multi-agent approaches for testing and validation
• Database management experience: PostgreSQL, RDS
• Core stack: Python. Helpful: Spark/PySpark, Scala, and other large-scale data tooling
• Experience with large data pipelines, high-performance computing, and Spark/PySpark
• Solid AWS cloud management experience
• Knowledge-graph and ontology frameworks (e.g., Neo4j)
• Self-driven, mission-driven, curious, and constructive — a startup mindset with strong communication skills
• Ability to provide references and meet in person