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The engine is committed to maintaining a strict latency SLA (p99<500ms) and a 5-nines availability rating. For each decision we run an unusually large data enrichment topology that encapsulates the combined and accumulated knowledge of Forter's analytical staff and upstream cyber capabilities.

The team lives in a highly technical backend domain, where the roadmap is composed of product-led and engineering-led initiatives in roughly equal parts.
Along with the engine itself, the team owns the API entry point into Forter, and the development process that allows analysts to build the engine using a self-service approach.
The team is extremely central in Forter's business day-to-day, and many of the challenges in the team arise from that centrality.

Given that the role requires active participation in the roadmap setting, you will need an investor "tool-set" that includes developing a solid and nuanced understanding of Forter's business value and the ability to zoom in/out on the details (including technical details) while always keeping an eye on ROI and risk. You'll need to be an innovator in spirit, that knows the power of a simple and well thought out piece of software to solve big business problems.

What you'll be doing:
Own one of our most business-critical areas. Oversee its development to ensure SLAs and long-term quality
Guide top-tier engineers (including Staff+) on how to plan and execute projects that carry a lot of technical risk (risk of ballooning investments) and precision/product risk (bad ROI)
Guide engineers on how to develop their business-value understanding, and how to channel their innovation towards the places that move the needle the most from a business perspective
Innovate around the engine's capabilities, APIs and the agentic interfaces that it offers our customers. Be opinionated around the engine's product-space

Were on a mission to build the first holistic smart payment solution-one that maximizes authorization rates for our merchants by intelligently determining and executing the optimal strategy for every transaction. Our Payments team is designing and running highly critical, production-grade infrastructure, and were looking for a deeply technical engineer to help shape it from the ground up.

In this role, youll lead the design and development of payment products, build resilient infrastructure, dive deep into technical complexity to solve production challenges, and work closely with teammates, stakeholders, and customers to understand their needs. Youll have end-to-end ownership-from architecture and coding to deployment and monitoring-while helping set the technical direction for a growing initiative.

This is an early-stage effort, giving you the chance to be a founding member, influence architectural decisions, and directly impact merchant success. We value thoughtful technology choices, resourcefulness, and a fast-moving, problem-solving mindset. Our engineers are creative, independent, and adaptable, working with a diverse stack of technologies to deliver maximum value to our clients.


What you'll be doing:
Build and enhance payment products-creating new systems from scratch while improving and integrating with existing ones.
Design and implement resilient, production-grade infrastructure that can handle critical workloads.
Lead technical initiatives within the Payments team, collaborating with teammates and stakeholders across us.
Work across a diverse tech stack and programming languages.
Brainstorm and shape features with product managers and peers, guiding decisions with your technical expertise.
Work closely with customers to understand their needs and translate them into impactful payment solutions.
Mentor and support fellow engineers.
Dive deep into technical complexity to diagnose and solve production issues.
Take initiative-if you see a way to make our systems or workflow better, own it and make it happen.

We are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.


What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across Forters decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are looking for a Staff engineer to join our Data Products team.

The team owns the data platform layer underneath our core operations.

It builds and operates the real-time data processing systems, quality pipelines, schema infrastructure, and knowledge base tooling that make agent-driven work trustworthy at scale.


What you'll be doing:
Design, build, and operate Flink-based streaming pipelines at production scale, the real-time processing systems at the core of our internal workflows.
Own data quality and observability infrastructure: schema contracts, freshness monitoring, ownership registries, and the alerting systems that catch problems before they affect downstream processes.
Build and evolve the knowledge base tooling that makes institutional context queryable for agents and engineers.
Drive data integrity work: design systems that recover reliably from failure and make the underlying platform trustworthy by default.
Collaborate with the Agentic Data Foundation initiative as we build a company-wide data layer; Data Products is where the proof of concept gets built and validated.
Set technical direction across the team's systems and hold architecture standards with the EM and other Staff engineers.

were looking for a passionate Tech Lead to join our collaborative team.

Youll be at the forefront of innovation-designing scalable solutions, guiding architecture, and driving technical excellence as we deliver world-class experiences to millions of sports fans around the globe.

Responsibilities
Design robust APIs and services for a vast user base
Architect and guide performance optimization, security, and scalability strategies
Analyze and process large datasets in near real-time to deliver insight
Oversee data pipelines that power real-time push notifications for a global user base
Provide a technical specification for complicated features
Support development team, delegate tasks, and resolve technical blockers
Perform code reviews to ensure best practices are followed and offer constructive feedback for continuous improvement.
Ensure high code quality, maintainability, and test coverage (unit/integration tests)
Own the delivery of releases all the way to production
Help manage hiring process and onboarding of developers

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards