{"id":20714,"url":"https://alion.io/job/sift-forward-deployed-engineer-trust-and-safety","title":"Forward Deployed Engineer, Trust and Safety","company":{"id":5870,"name":"Sift","domain":"sift.com","url":"https://alion.io/company/sift","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":230000,"currency":"USD","period":"year","gross":null,"usd_annual":230000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"LLM","optional":true},{"name":"Machine Learning","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-06-30T00:10:35Z","employer_posted_date":"2026-08-01","last_verified_at":"2026-10-17T18:10:58Z","board_verified":true,"closed_at":null,"days_open":109,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":109},"description":"About the Team:\nWe’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.\nWhat you’ll do:\nWork with our Trust and Safety Architect and Data Science teams to surface emerging fraud patterns across the network escalate and proactively take them down.\n\nDetect patterns and turn those findings into sharper signals, tighter configurations, and smarter decisioning logic.\n\nWork 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.\n\nHelp build dashboards, tune and build models, decision logic and custom signals to help customers achieve their desired business outcomes\n\nIdentify 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\n\nLead forensic investigations during fraud spikes: trace attack patterns to their source, identify the technique being used, deliver a clear writeup with remediation steps\n\nDistinguish between one-off anomalies and systemic gaps that indicate a product opportunity - and advocate for the latter with rigor\n\nContribute to detection frameworks, investigative tooling, and internal playbooks that make every engineer and analyst at Sift more effective\n\nBe the conduit between customer reality and internal roadmap; your field observations should directly accelerate what Sift ships next\n\nSome travel may be required\n\nWhat We're Looking For\nRequired\n5 - 8 years in fraud, trust & safety, risk, or a closely related data science domain - you've spent meaningful time working with fraud data, not just adjacent to it\n\nStrong SQL and Python skills; you reach for code to answer a question, not to build a pipeline\n\nStrong understanding of ML concepts applied to fraud: classification models, feature engineering, precision/recall tradeoffs, threshold calibration, score drift\n\nExperience 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\n\nAbility 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\n\nCustomer-facing experience; you understand that different businesses have different priorities, and that listening before optimizing is part of the job\n\nNice to Have\nHands-on experience with fraud detection platforms (in house or 3rd party)\n\nHands-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\n\nFamiliarity with real-time event processing systems\n\nExperience with rules-based decisioning systems alongside ML - knowing when a hard rule beats a model score\n\nBackground in payments, e-commerce, fintech, marketplace, or account security fraud\n\nPrior forward deployed, staff engineering, or embedded consulting experience at a technical product company\n\nComputer Science, Data Science, Mathematics, Statistics, Information Systems, Economics degree or equivalent\n\nLet’s build it together:\nAt Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community - ultimately using this empowerment and authenticity to build trust and create a safer Internet.\nThis document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy\nA little about us:\nSift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.","description_format":"text","description_chars":4932,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fraud Detection","Cybersecurity AI"],"lifecycle":[{"event":"open","at":"2026-06-30T00:10:35Z"}],"visa":[],"liveness":{"score":12,"band":"cold","label":"Long shot","p_open":1,"p_active":0.413,"p_room":0.28,"age_days":109,"expected_fill_days":49,"reasons":["conf:0","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":230000,"is_top_pay":true},"html_url":"https://alion.io/job/sift-forward-deployed-engineer-trust-and-safety","json_url":"https://alion.io/job/sift-forward-deployed-engineer-trust-and-safety.json","meta":{"generated_at":"2026-10-17T18:21:13Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":1029,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":5870},"rest":"https://alion.io/mcp/rest/get_company?id=5870"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsift-forward-deployed-engineer-trust-and-safety"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fsift-forward-deployed-engineer-trust-and-safety"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fsift-forward-deployed-engineer-trust-and-safety"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/sift-forward-deployed-engineer-trust-and-safety\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsift-forward-deployed-engineer-trust-and-safety"}]}