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Sift

AI-driven real-time fraud prevention for e-commerce

Technical Account Manager

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeRemote in USA$115k - $155.5k /yrRemote

About the Job

Requirements

  • At least 5 years of experience in a technical, customer-facing role such as Technical Account Management, Solutions Engineering, Implementation, or Technical Support.
  • Prior experience in fraud or payments.
  • Strong pattern recognition across application programming interfaces, webhooks, JSON, and data logs, including the ability to identify anomalies and diagnose root causes.
  • Working SQL and data analysis skills, or the ability to develop them quickly, to pull and interpret account-specific data.
  • Familiarity with scripting languages; Python is a plus.
  • Ability to translate technical details into business impact for hands-on engineers and non-technical stakeholders.
  • A structured, proactive approach to account health and catching workflow issues before escalation.
  • Ability to operate under pressure during live incidents and communicate clearly and calmly with customers.
  • Ability to augment a work process using AI tooling.
  • Ability to coordinate cross-functionally with Support, Customer Engineering, TASA, and Product.
  • Familiarity with machine learning concepts sufficient to explain model behavior, score changes, and release impact to customers.
  • Experience running formal technical health reviews, QBR-style technical readouts, or success-planning cadences.

Responsibilities

  • Serve as the named, persistent technical partner for a portfolio of strategic and premium accounts in close alignment with the CSM.
  • Build and maintain a technical success plan for each account alongside the CSM, translating technical diagnostics into business value stories and executive roadmaps.
  • Diagnose and guide customers on best practices for workflow design, labeling strategy, and configuration hygiene, using patterns across the account portfolio in tandem with the CSM.
  • Own implementation continuity after go-live with the CSM, preserving account context through onboarding handoffs and identifying technical drift early.
  • Run recurring technical health reviews and diagnostic readouts with the CSM, surfacing risks and developing optimization plans.
  • Help customers navigate model releases by analyzing score behavior changes and explaining their implications for customer business goals.
  • Operationalize TASA fraud strategy and vertical recommendations within customers' Sift environments with the CSM, demonstrating business impact.
  • Coordinate technical diagnosis and mitigation during active fraud attacks, orchestrating Support, Customer Engineering, and Product while keeping the CSM and customer informed.
  • Identify recurring technical patterns, feature requests, and workflow trends across accounts and communicate them to Product and Engineering.
  • Act as the primary technical partner to the CSM across Support, Customer Engineering, TASA, Managed Operations, and Product/Engineering.
  • Contribute to account retention and growth by identifying technical risk early, preparing accounts for model releases, and reducing repeat issues in partnership with the CSM.

About the Company

Sift

AI-driven real-time fraud prevention for e-commerce

Sift builds a Digital Trust & Safety platform that helps e-commerce and fintech companies prevent fraud while keeping legitimate customers moving. It uses machine learning and AI to analyze vast streams of data in real time, delivering risk scores and decisions that integrate with clients’ existing systems. The platform provides dynamic friction—allowing valid transactions to proceed smoothly while stopping fraudulent ones—and it scales across small online retailers to large financial institutions. Revenue comes from a subscription model plus consulting and custom integration services. Sift’s goal is to reduce chargebacks and account takeovers, protect customer trust, and support safe digital commerce at scale, by delivering precise, real-time fraud prevention without disrupting normal user experiences.

Company size
201-500
Company stage
Series E
Total funding
$156.7M
Headquarters
San Francisco, CA
Founded
2011

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