AI Data Engineer

As an AI Data Engineer on Quantifind’s AI Systems team, you’ll drive data prototyping and experimental ETL pipelines 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 Benefits Meaningful equity to full-time employees Performance reviews conducted twice per year, with opportunities to advance Collaboration across departments - there’s always an opportunity to work on the projects you care most about We encourage people to hone their crafts by taking classes and attending conferences We pay 95% of your premiums with top medical, dental and vision plans for you and your family, plus other benefits including FSAs and life insurance We match employee retirement contributions dollar-for-dollar up to 4% after your first year Flexible hours and a flexible vacation policy Remote or in-office options Qualities & Expectations You bring a data architecture mindset, and are focused on ontologies, frameworks, documentation, and unifying value across heterogeneous sources into knowledge graphs. You’re also an engineer who codes with AI as a first-class tool, not an add-on. You’re comfortable managing complexity across both structured and unstructured pipelines, and you’re genuinely curious about data: its provenance, its quality, and its ultimate value to customers. You move fast, iterate with stakeholders, and care about shipping things that work. You are familiar with investigative products built on open-source intelligence. You’ve built and managed large-scale ingestion pipelines from discovery through to performant products in high-stakes systems. You are an experienced data engineer with a modern AI tooling perspective. You pair traditional technical training with a forward-leaning approach to agentic coding, rapid prototyping, and multi-agent workflows. You have a responsible mindset and are familiar with the legal and compliance limits on data use. Experience with large data pipelines, high-performance computing, and Spark/PySpark. Ability to provide references and meet in person. Self-driven, mission-driven, curious, and constructive — a startup mindset with strong communication skills. Core Stack Core stack: Python. Helpful: Spark/PySpark, Scala, and other large-scale data tooling. Experience & Education Solid AWS cloud management experience 4+ years of professional experience, including graduate or Ph.D. work if relevant. Required Skills Technical education Knowledge-graph and ontology frameworks (e.g., Neo4j) Forward-leaning in AI coding, with traditional technical training as a foundation Database management experience: PostgreSQL, RDS Hands-on with AI coding tools and agentic workflows (Claude Code, GPT/Codex, Cursor, Windsurf), including multi-agent approaches for testing and validation US Citizen #J-18808-Ljbffr