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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # TELECOMMUTE - **Company:** Sift - **Location:** San Francisco, CA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Information Systems, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Raw Data, Standard Sql, Feature Engineering, Large Language Models, Prompt Engineering, Information Technology, Build Tools, Marketplace - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/f2223cb0-9a3e-425d-b680-e95c0f4cc5f4 ## About the Role * 5-8 years in fraud, trust & safety, risk, or a closely related technical domain - you've spent meaningful time working with fraud data, not just adjacent to it * Strong SQL and Python skills; you reach for code to answer a question, not to build a pipeline * Hands-on experience building with AI: LLM APIs, prompt engineering, or agentic workflows - whether that's automating an investigation step, building a tool that surfaces patterns from raw data, or wiring together a multi-step agent to accelerate fraud analysis * Strong understanding of ML concepts applied to fraud: classification models, feature engineering, precision/recall tradeoffs, threshold calibration, score drift * Experience analyzing large-scale behavioral or transactional datasets to find patterns and anomalies - you know what a fraud ring looks like in the data, not just in a textbook * Ability to communicate technical findings to both technical and non-technical stakeholders; you can write a forensic investigation report and present it to a VP of Risk in the same week * Customer-facing experience; you understand that different businesses have different priorities, and that listening before optimizing is part of the job * Ability to travel up to 30% Nice to Have * Hands-on experience with fraud detection platforms (in house or 3rd party) * Familiarity with real-time event processing systems * Experience with rules-based decisioning systems alongside ML - knowing when a hard rule beats a model score * Background in payments, e-commerce, fintech, marketplace, or account security fraud * Prior forward deployed, staff engineering, or embedded consulting experience at a technical product company * Computer Science, Mathematics, Statistics, Information Systems, Economics degree or equivalent ## Description We're people that are passionate about making the internet a safer and more trusted place for all. We love the fraud and trust & safety space and want to teach companies how they can protect themselves, their users and create frictionless experiences for legitimate consumers. As a Forward Deployed Engineer, Trust and Safety, you are heavily experienced in detecting and acting on multiple types of online abuse from a technical and quantitative perspective. You've helped build tools, models and detection platforms at companies that have had to work through these threats at a global level. What you'll do: * Work with our Trust and Safety Architect and Data Science teams to surface emerging fraud patterns across the network escalate and proactively take them down. * Detect patterns and turn those findings into sharper signals, tighter configurations, and smarter decisioning logic. * Work across different verticals and closely with customers, partners and prospects with different risk appetites - some optimizing for approval rates, some minimizing chargebacks, some fighting account takeover and other types of abuse. * Help build dashboards, tune models, decision logic and custom signals to help customers achieve their desired business outcomes * Identify sources of false positives, possible coverage gaps and other vulnerabilities by digging into raw event streams; form a hypothesis, design a test and implement the fix * Lead forensic investigations during fraud spikes: trace attack patterns to their source, identify the technique being used, deliver a clear writeup with remediation steps * Distinguish between one-off anomalies and systemic gaps that indicate a product opportunity - and advocate for the latter with rigor * Contribute to detection frameworks, investigative tooling, and internal playbooks that make every engineer and analyst at Sift more effective * Be the conduit between customer reality and internal roadmap; your field observations should directly accelerate what Sift ships next ## Related Videos - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Launching a marketplace on-time: A lesson in taking shortcuts using spreadsheets!](https://www.wearedevelopers.com/videos/477-launching-a-marketplace-on-time-a-lesson-in-taking-shortcuts-using-spreadsheets) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) - [Building a framework-independent component library](https://www.wearedevelopers.com/videos/1679-building-a-framework-independent-component-library) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)