Engineering Manager

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients' success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy. Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values [here](https://www.signifyd.com/about/#values)! ### Role Overview Signifyd uses the latest in AI and machine learning technology to give our ecommerce customers the confidence they need to do business free from fears of fraud and other forms of ecommerce abuse. In order to do this we have to continually innovate and nowhere is this more important than in our modeling space. The modeling group creates, deploys and runs the models and services that keep us a step ahead and right now we need an engineering manager to help us build our next generation technology. The successful candidate will lead a team of engineers who will partner with our AI group and engineering as a whole to help bring ideas from conception to production, while ensuring the systems we already have continue to run smoothly. It's a role for someone who can operate comfortably on both sides of the technical/business line, contributing to technical discussions but people-focused enough to build the relationships between engineering, our AI lab, product and our risk management organization. You will work daily with data scientists, machine learning engineers, product owners and other cross-functional stakeholders whose work depends on your team's systems. Success means being a trusted translator and partner across all of these groups, not just a manager of your own team's output. Your core responsibilities are delivery, fostering innovation and people leadership. How hands-on you get as part of that is up to you but you will be expected to drive closure on technical decisions and implementation. ### Key Responsibilities (outcome and accountability) #### 1. Team Leadership & Growth - Manage, coach and grow a team of engineers, providing regular feedback, career development while ensuring performance remains high. - Build a healthy team culture with clear ownership, sustainable pace and high standards for quality and craftsmanship. - Recruit and onboard new engineers as needed and develop technical leadership within the team. #### 2. Stakeholder & Relationship Management - Manage competing priorities and expectations across multiple stakeholder groups, building trust through fostering mutual understanding, delivering consistently and communicating transparently. - Represent the team's roadmap, capacity and risks in cross-functional planning and prioritization discussions. #### 3. Technical Engagement & Decision-Making - Drive technical discussions and design reviews, with enough depth to understand the implications of key decisions on reliability, scalability and production outcomes. - Partner with engineers on architecture and design choices, asking the right questions rather than dictating solutions. - Ensure the team's technical decisions are well understood by, and defensible to, other stakeholders. #### 4. AI-Enabled Ways of Working - Model and champion effective use of AI tools across the team's day-to-day work, including AI-assisted research, administrative workflows, and code generation. - Help the team develop good judgment about how to balance the productivity gains AI can bring against the risks it introduces. - Continuously look for ways AI tooling can improve team efficiency, code quality, and decision-making, and share what's working with peers. - Manage effectively through the major changes AI is bringing to the industry. #### 5. Delivery & Operational Rigor - Own delivery of the team's roadmap balancing feature work, technical debt and reliability commitments. - Establish and maintain appropriate quality, testing and monitoring practices. - Provide clear, proactive communication on progress, risks and blockers to stakeholders and leadership. - Define metrics as needed and develop an understanding of why we did or didn't hit our targets. ### Qualifications & Skills (experience / depth) #### Experience - 5+ years working as a software engineer. Some of that experience should be in the ML sphere. - This should not be your first time managing and we'd prefer at least 4 years of experience managing engineers directly in an ML focused domain. #### Technical & AI Fluency - Comfortable engaging in technical discussions on architecture, data flows, and system design. - Dem