Engineering Manager
Signifyd · USA
About this role
## Engineering Manager ### About Signifyd Signifyd helps merchants confidently grow by building trusted relationships with their customers. Our technology enables frictionless shopping experiences—approving more good orders, protecting revenue, and keeping customers happy—while helping online retailers eliminate fraud and improve customer experience. ### Role Overview Signifyd uses AI and machine learning to give ecommerce customers confidence to do business without fears of fraud and other ecommerce abuse. The Modeling group creates, deploys, and runs the models and services that keep us ahead. As an Engineering Manager, you’ll lead a team of engineers and partner closely with our AI group and engineering to take ideas from conception to production—while ensuring existing systems continue to run smoothly. You’ll operate comfortably across both technical and business lines: contributing to technical discussions and building strong relationships across engineering, the AI lab, product, and risk management. ### Key Responsibilities - **Team Leadership & Growth**: Manage, coach, and grow engineers; provide feedback and career development; build a healthy culture with clear ownership, sustainable pace, and high quality. - **Stakeholder & Relationship Management**: Manage competing priorities; build trust through transparent communication; represent roadmap, capacity, and risks in cross-functional planning. - **Technical Engagement & Decision-Making**: Lead technical discussions and design reviews; understand implications for reliability, scalability, and production outcomes; partner on architecture and design choices. - **AI-Enabled Ways of Working**: Champion effective use of AI tools for research, workflows, and code generation; help the team balance productivity gains with responsible risk management. - **Delivery & Operational Rigor**: Own the team roadmap across feature work, technical debt, and reliability commitments; establish quality/testing/monitoring practices; communicate progress, risks, and blockers. ### Qualifications & Skills - **Experience**: 5+ years as a software engineer; some experience in the ML sphere. Prefer 4+ years managing engineers directly in an ML-focused domain. - **Technical & AI Fluency**: Strong ability to engage in architecture, data flows, and system design discussions. Demonstrated professional use of AI tools (research, administration, code generation) with a responsible, cost-effective approach. - **MLOps & Reliability**: Best practices in software development, cloud platforms, big data technologies, MLOps toolkits, and SLO-driven reliability management. - **Preferred Tools/Stack**: Experience with at least one of Databricks, Spark, Airflow, Vertex, and the GCP ecosystem. - **Stakeholder Management & Communication**: Proven ability to communicate clearly across technical and non-technical audiences; influence without authority; manage competing priorities. - **Leadership**: Genuine care for engineer growth; experience providing structured feedback and building career paths; build trust and psychological safety while maintaining high standards. ### Benefits (US) - Discretionary Time Off Policy (Unlimited!) - 401K Match - Stock Options - Annual Performance Bonus - Paid Parental Leave (12 weeks) - On-Demand Therapy for employees & dependents - Dedicated learning budget through Learnerbly - Health, Dental, and Vision Insurance - Flexible Spending Account (FSA) - Short Term & Long Term Disability Insu
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