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Forter Tech Stack
AI-powered identity and fraud assessment for high-volume digital commerce
Forter processes identity and fraud decisions across digital commerce at scale, using Python, Java, and Apache Spark on AWS + Kubernetes infrastructure. The tech stack shows a mature streaming and ML backbone (Flink, Spark, Cassandra, Aerospike) now being modernized—they're adopting observability tools (Mimir, Grafana, Honeycomb, Loki) and RAG, while phasing out Elasticsearch. The hiring mix skews senior (30 of 69 roles) with engineering-heavy demand, signaling both complexity in production decisioning logic and a shift from pure fraud detection toward broader commerce optimization.
Tech Stack 77 technologies
Core StackSalesforce JavaScript Salesloft Python Java Kotlin Node.js AWS Kubernetes Docker Apache Flink MATLAB Apache Spark TypeScript GraphQL Shopify Magento MySQL PostgreSQL MariaDB Cassandra Outreach LinkedIn Sales Navigator SQL API Gateway Storm R Salesforce Commerce Cloud Commercetools Aerospike+41 more
ReplacingElasticsearch
What Forter Is Building
◆Challenges
- Escalations and incidents
- Improving response times
- Fast onboarding of merchants
- Fraud detection in e-commerce
- Transitioning from fraud prevention to e-commerce optimisation
- Emerging global threats
- Scaling self-service analytics
- High-scale low-latency components
- Improving architecture for faster onboarding
- Expanding payments optimisation
▲Active Projects
- Resilient infrastructure
- Self-service analytics & ml platform
- Maintaining merchant business rules
- Platform extensions for merchant onboarding
- Policy builder customer education
- Payment products
- Implement ai guardrails and evaluation frameworks
- Build infrastructure for autonomous and interactive agents
- Live production decisioning logic improvement
- Account-based marketing strategy
Hiring Activity
Steady70 roles · 25 in 30d
Department
Seniority
Notable leadership hires: Director of Engineering, Strategic Alliances Director
Company intelligence
