Engineering Manager | Payments, Abuse, and Conversion

DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. You will be joining the PAC (Payments, Abuse & Conversion) team, part of the BAT (Business Acceleration Technology) organisation within DeepL's Monetisation track.

Responsibilities

Lead, mentor, and grow a distributed team of engineers across varying seniority levels, owning their well-being and development through regular 1:1s, continuous feedback, performance reviews, and dedicated career development coaching; Own the team's delivery cadence, establishing a predictable and healthy agile process, and partner with the Product Manager to define, refine, and prioritise the quarterly roadmap; Act as the team's technical steward, guiding architectural decisions across PAC's payments and fraud infrastructure, reviewing system designs, and upholding high standards for quality, scalability, reliability, and security; Hold the strategic balance between conversion optimisation and fraud prevention, making pragmatic, data-informed trade-offs across activation, retention, bot protection, rate limiting, and abuse detection to protect DeepL's revenue while minimising friction for legitimate users; Serve as PAC's primary representative in planning and cross-functional discussions, articulating technical trade-offs in commercial terms, building strong relationships with product, finance, and engineering stakeholders, and ensuring the team's work is understood and valued across the organisation

Requirements

Proven experience in direct people management, leading engineering teams through growth, performance challenges, and organisational change; Significant hands-on experience as a Senior or Staff-level backend engineer, with the depth to guide architectural discussions and earn credibility with a senior team; Proven hands-on experience building or managing payment gateway integrations, checkout flows, or billing infrastructure at production scale; Sufficient depth in fraud prevention, abuse detection, rate limiting, or bot protection to guide architectural decisions across a complex, multi-layered fraud stack; Proven experience designing, building, and operating scalable, highly available distributed systems in a cloud-native environment; Demonstrable experience with cloud platforms (preferably AWS), containerisation (Docker, Kubernetes), and API design (gRPC, REST); Hands-on experience with both relational and NoSQL databases; Deep commitment to the growth and well-being of your team, with proven experience in coaching, mentorship, and performance management; Comfort interrogating funnel metrics, conversion data, and fraud loss reporting to drive prioritisation decisions and communicate impact to stakeholders; A pragmatic approach to balancing technical excellence with the practical need to ship, with a track record of delivering in high-stakes, fast-moving environments

Nice to have

Familiarity with machine learning-based fraud detection or risk scoring systems; Demonstrated experience with event-based processing and messaging systems such as Kafka; Experience owning or contributing to activation, retention, or monetisation metrics in a B2C or PLG SaaS context; Proven track record of hiring and onboarding software engineers in a distributed team environment; Strong experience with CI/CD pipelines, infrastructure scaling, and cloud migration

Benefits

Becoming part of a large, global community with people of more than 90 nationalities; Open communication and regular feedback with a focus on clear, honest communication; Hybrid work schedule with flexible hours and team members coming into the office twice a week; Virtual Shares giving every employee an ownership mindset; Regular in-person team events including local team and business unit gatherings and company-wide events; Monthly full-day hacking sessions (Hack Fridays); 30 days of annual leave excluding public holidays and access to mental health resources; Competitive benefits package tailored to location