Job Opportunities API

Shape the future of trust in the age of AI At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place https://oscilar.com/careers. WHY JOIN US: - Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer. - Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward. - Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk. THE ROLE: AML operations teams are making high-stakes decisions on bad tooling. False positive rates hitting 90–95%. SAR narratives written by hand. Alert queues backlogged for days. Investigation workflows duct-taped across a transaction monitoring system, a case management tool, and a spreadsheet no one owns. AI has gotten good enough to fix most of this - but compliance teams don't trust it yet, and most AI vendors don't understand AML well enough to earn that trust. You will own the product that earns it. At Oscilar, you'll have full product ownership of our AML and financial crimes suite: transaction monitoring, KYC/KYB, screening, case management, SAR filing, and the AI agents that are beginning to augment and automate the investigation workflow itself. This is not a handed-down playbook. You are writing it. WHAT YOU'LL OWN: - Transaction Monitoring. The rules engine and ML model layer that generates alerts - scenario design, threshold calibration, typology coverage, backtesting against historical transaction data. You'll define what the system flags, why, and how those decisions evolve as customer behavior and fraud typologies shift. You understand the difference between a rules-based velocity check and a graph-based network detection model, and you have opinions on when each is right. - KYC / KYB. Onboarding risk workflows: identity verification, document checks, beneficial ownership, ongoing monitoring triggers, and risk re-scoring. You know the data sources that power these decisions - bureau data, device signals, open banking, registry data - and how to orchestrate them dynamically based on risk tier rather than applying a one-size waterfall. - Screening. Sanctions (OFAC, UN, EU), PEPs, adverse media, and negative news. You understand the matching problem - why fuzzy matching on names produces the false positive rates it does, and what it takes to make screening defensible to an examiner without generating alert volumes that bury the ops team. - Case Management. The workflow layer: alert routing, case assignment, escalation logic, analyst productivity tooling, QA/QC review, disposition tracking. You think about this as a human-in-the-loop system design problem - where humans add the most value and where AI can carry the load. - SAR Filing & Regulatory Reporting. FinCEN SAR workflow end-to-end: narrative generation, supporting documentation, filing status, audit trail. You've seen what regulators look for in an MRA and you build product that holds up under that scrutiny. - AML Data Strategy. The data model that powers all of the above: transaction graphs, entity resolution, behavioral baselines, consortium signals, model feature pipelines. You can speak fluently to a data engineer about what data the models need and why, and to a compliance officer about what the model's output means and how it was derived. HOW YOU'LL WORK: - You are an AI-native PM. You use AI tools throughout your entire workflow — not as a novelty, but as a force multiplier that lets you do in a day what used to take a week. - For discovery: You use AI to synthesize call transcripts