Job Opportunities API

Who You Are You are an experienced data engineer with a modern AI tooling perspective. You've built and managed large-scale ingestion pipelines from discovery through to performant products in high-stakes systems. You bring a data architecture mindset, and are focused on ontologies, frameworks, documentation, and unifying value across heterogeneous sources into knowledge graphs. You are familiar with investigative products built on open-source intelligence. 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 have a responsible mindset and are familiar with the legal and compliance limits on data use. You're also an engineer who codes with AI as a first-class tool, not an add-on. You pair traditional technical training with a forward-leaning approach to agentic coding, rapid prototyping, and multi-agent workflows. You move fast, iterate with stakeholders, and care about shipping things that work. Who We Are Quantifind helps some of the world’s biggest banks catch money laundering and fraud. Quantifind also works with government agencies to use the same platform to uncover criminal networks and combat money laundering committed by internationally sanctioned entities. Unlike other players in this space, Quantifind delivers results as software-as-a-service (SaaS) with consumer-grade user experiences.  Quantifind is a data science technology company whose AI platform uncovers signals of risk across disparate and unstructured text sources. In financial crimes risk management, Quantifind’s solution uniquely combines internal financial institution data with public domain data to assess risk in the context of Know Your Customer (KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML) processes. Today these compliance processes are burdened by ever-increasing regulatory responsibilities and an expectation of frictionless transactions. Legacy technologies demand increasingly more human resources as the operations expand; Quantifind’s SaaS solution offers a way to cut through the inefficiency and enhance effectiveness simultaneously.  To help you succeed, we provide a supportive environment that fosters collaboration between teams and team members, where learning and professional growth are considered a key part of your success, and of ours. We offer a flexible work environment with a family friendly work-life balance. What a Great Candidate Looks Like 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 The Opportunity We Offer As an AI Data Engineer on Quantifind's AI Systems team, you'll drive data prototyping and experimental ETL pipelines. Data Engineering:  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 a