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Fig Security Tech Stack
Security operations platform for detecting and fixing broken detection workflows
Fig builds tooling to keep security operations running through infrastructure and process changes. The stack is Python + Node.js on Kubernetes across AWS and GCP, with Neo4j for graph-based security flow modeling and LangGraph/LangChain for AI-driven analysis — a modern approach to the historically manual work of validating detection rules and response playbooks. Early-stage hiring is split between engineering and go-to-market, with active projects spanning production AI agents, low-latency API design, and sales methodology — typical for a seed/Series A company hardening product-market fit.
Tech Stack 19 technologies
Core StackPython Node.js PostgreSQL Neo4j AWS Kubernetes Docker Terraform LangChain AWS RDS Pulumi GitHub Actions GitLab CI/CD Jenkins GCP LangGraph VPC AWS EKS Bash
What Fig Security Is Building
◆Challenges
- Broken security flows
- Zero-to-one growth phases
- Demand generation
- Sales infrastructure development
- Scaling backend services
- High-concurrency user demands
- Architectural bottlenecks
- Scalable secure resilient platform
- Multi-cloud strategy implementation
- Infrastructure ci/cd pipeline ownership
▲Active Projects
- Sales pipeline development
- Global go-to-market strategy
- High-performance sales organization
- Sales engine architecture
- Product launch content
- Market research and analyst submissions
- Building production-grade ai agents
- Designing low-latency apis
- Optimizing database performance
- Inaugural sales methodology and playbook
Hiring Activity
6 roles · 6 in 30d
Department
Seniority
Company intelligence
