Senior Engineering Manager, Risk Platform

Trustly is hiring a Senior Engineering Manager, Risk Platform in San Francisco, United States. It pays $226k-$340k a year and Level rates it ; you can apply on Trustly.

Level's read on this job

Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
The posting allows some remote work.
Tools and skills the posting cites include CI/CD, engineering management and risk management.
Level lists 33 other open roles at Trustly.
The role was posted within the past week.

AI in this role

Lead the engineering team building real-time payment risk decision platforms and deploying data science models to production.

ci-cd

engineering-managementrisk-managementmachine-learning

WHO WE ARE

At Trustly, we're building a smarter, faster, and more secure financial future by revolutionizing the world of payments. As a global leader in Open Banking Payments, we are establishing Pay by Bank as the new standard at checkout, providing unparalleled freedom, speed, and ease to millions of consumers and merchants worldwide.

Our Ambition: To build the world’s most disruptive payment network and redefine what the payment experience should feel like.

Trustly is a global team of innovators, collaborators, and doers. If you are driven by a strong sense of purpose and thrive in a dynamic, entrepreneurial, and high-growth environment, join us and be part of a team that’s transforming the way the world pays.

ABOUT THE ROLE

Trustly guarantees payments in North America, and every approval and recovery decision runs on our risk decisioning platform. You’ll lead the engineering team that builds and runs it: its architecture, reliability and modernization, and the path that takes Data Science models into production. You’ll work closely with Risk Product Management, which owns the product roadmap, and with Data Science and payments engineering.

WHAT YOU'LL DO

Platform strategy and architecture

Set the technical strategy and roadmap for the risk engine with Risk Product Management and Data Science.
Own the architecture of the real-time decisioning platform. Make and document the trade-offs on latency, availability, cost and auditability.
Lead the modernization of the risk engine, including a configuration-driven rules framework with versioning, testing and approval controls.
Partner with Data Science to deploy models into the risk engine using shadow mode and champion/challenger testing.

DELIVERY AND OPERATIONS

Turn the product roadmap into team plans. Agree scope, order and capacity with Product, Data Science, Risk Management and Payments engineering.
Own delivery and release management: CI/CD, release coordination, go/no-go decisions and rollback. Track DORA metrics and fix bottlenecks.
Own reliability for a system on the critical payment path: SLOs, observability, on-call, incident response and blameless postmortems.
Make sure every risk decision is logged, versioned and reproducible for audits, customer inquiries and loss investigations.

LEAD THE TEAM

Hire, coach and develop engineers and tech leads. Give direct feedback and manage performance.
Spread ownership and system knowledge across the team so the team has no single points of failure.
Explain technical decisions, risks and trade-offs clearly to senior leaders, Product and Commercial teams.

WHAT WE'RE LOOKING FOR

10+ years in backend software engineering, including 4+ years managing engineers.
Experience owning a real-time, high-availability decisioning system in production, such as a fraud, risk, credit or payment authorization platform.
Strong Java or Kotlin and a background in distributed systems. You can review code and designs and challenge them.
Experience with rule engines, model serving and real-time scoring, including putting ML models into production.
A track record of modernizing a business-critical platform while it stays in service.
Experience owning CI/CD and releases for production services, and using delivery and reliability metrics to improve the team.
Product sense: you can shape a roadmap with Product, push back on scope and decide what not to build.
Clear written and verbal communication with engineers, data scientists and senior leaders.

PREFERRED

Payments, fraud or credit risk domain experience, ideally ACH or EFT.
Understanding of how rules, thresholds and model scores together drive approval rate, loss and conversion.
Experience building controls in a regulated financial environment, such as change management, decision logs and model governance.
Experience leading teams across time zones in the Americas and Europe.
Bachelor’s degree in Computer Science or a related field, or equivalent experience.

LOCATION AND WORKPLACE

This role is based in San Francisco or New York, with 3 days a week in the office.

How we rate this

Senior Engineering Manager, Risk Platform at Trustly rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Engineering Manager, Risk Platform is an open job at Trustly.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $226k-$340k a year.
The role is based in San Francisco and is marked remote.
The job was posted on October 20, 2026.
Seniority: senior.
Applications are handled by Trustly. Apply on Trustly

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Engineering ManagementRisk ManagementMachine learningCI/CD

Questions you could be asked

Tell me about a project where engineering management was part of your work. What did you do?
Tell me about a project where risk management was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
What's a project where you used CI/CD hands-on?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: Engineering Management, Risk Management, Machine learning, and CI/CD. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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