Jobs at Signifyd

Own the authorization optimization product roadmap, improving legitimate transaction approval rates and recovered merchant revenue. Define technical requirements, APIs, data models, integrations, and issuer-specific decisioning strategies. Partner with engineering, data science, sales, solutions, and customer success to deliver fraud-aware authorization improvements involving retries, 3DS, decline recovery, and payment routing. Manage partnerships with payment ecosystem providers, quantify opportunities using issuer and BIN intelligence, and communicate product strategy and performance to stakeholders.

Leads and develops a fraud analyst team responsible for investigating emerging threats, responding to incidents, and improving fraud-risk strategies. Owns investigative standards, playbooks, workflows, and tools while serving as an escalation resource for complex cases. Partners with Data Science, Customer Success, Product, Engineering, and business leaders to convert fraud insights into scalable signals, model improvements, and better customer outcomes. Supports customer conversations as a fraud subject-matter expert and coaches analysts on communicating risk decisions.

Senior Commercial Counsel will draft, review, and negotiate complex subscription, partnership, vendor, and other commercial agreements. The role primarily supports a global Sales organization, advises cross-functional teams, manages contracts managers, and handles enterprise and strategic partnership transactions. Responsibilities include balancing competing priorities, supporting legal projects, and providing practical, business-minded legal guidance in a fast-paced environment.

Engineering Interns contribute to software features across the full development lifecycle, including design, development, testing, deployment, monitoring, and improvement. They work with APIs, databases, streams, and queues while participating in stand-ups and peer-led teams. The role provides mentoring and hands-on experience with Signifyd’s technology stack. Candidates should be pursuing a bachelor’s degree in computer science or software engineering, show interest in software development and machine learning, and be curious, collaborative, and willing to learn.

Analyze and reconcile chargeback files across payment processors, investigate fraud, determine liability, process merchant reimbursement claims, gather transaction evidence, and dispute eligible cases. Support merchant onboarding, account configuration, policy compliance, quality assurance, and process improvements while collaborating with Customer Success, Product, Finance, banks, processors, and customers.

Provides post-sales technical account management and support for Latin American merchants. Responsibilities include leading e-commerce integrations, troubleshooting API and platform issues, coordinating escalations with internal teams, managing implementation milestones, maintaining CRM updates, training merchants, documenting best practices, and advising customer success and product teams. The role requires strong SaaS, e-commerce, API, technical support, communication, and stakeholder-management skills, plus fluent English and Spanish.

Investigate and process credit card chargebacks, reconcile processor files, determine liability, recover funds, and mitigate fraud losses. The role involves applying coverage policies, validating transaction evidence, onboarding and reviewing merchant accounts, troubleshooting data discrepancies, and collaborating with customers, banks, processors, Finance, Product, and Customer Success. Advanced Excel, payment processor, card network, research, and analytical skills are required.

Leads and develops an engineering team building, deploying, and operating machine-learning models and services for fraud prevention. Owns roadmap delivery, technical decisions, reliability, testing, monitoring, and stakeholder communication. Partners with data scientists, ML engineers, product, risk, and engineering teams. Drives responsible AI-tool adoption, recruits and coaches engineers, manages priorities, and ensures scalable, high-quality production systems.

Lead end-to-end ML projects for fraud detection: develop, deploy, monitor, and iterate production models and experimentation frameworks. Improve model performance, build scalable ML pipelines, collaborate with Product/Engineering/Risk, and champion testing, documentation, and model-monitoring best practices to ensure robust, high-impact solutions.

Lead design, implementation, and operation of Signifyd's GCP/Kubernetes cloud platform. Architect scalable, secure infrastructure, embed AI-driven automation, own SLOs and incident response, improve developer experience via CI/CD/GitOps tooling, mentor engineers, manage cloud capacity/FinOps, and build observability and security into the platform.

Lead and grow a machine learning engineering team responsible for fraud and risk models. Manage experimentation portfolios, balance research with delivery, evaluate model performance rigorously, and guide work through production release. Partner with Risk, platform, and infrastructure teams to set priorities, improve training and experimentation systems, communicate results, and make autonomous roadmap decisions. The role is a hands-on player-coach requiring technical depth, people leadership, strong communication, and comfort operating under uncertainty.

Lead and grow a distributed ML engineering team that runs experiments, ships production models, and partners with Risk and platform teams. Balance research bets and delivery, enforce rigorous evaluation and reproducibility, mentor engineers, own roadmap trade-offs, and represent results to stakeholders while improving model performance and production reliability.

Lead design and delivery of the public-facing API platform and ingestion services. Build scalable, reliable real-time distributed systems, collaborate with product and data teams, review designs and code, address technical debt, take operational ownership using observability tools, and mentor engineers.