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Alembic Technologies Tech Stack
Causal AI platform for marketing measurement and enterprise attribution
Alembic builds a causal inference engine focused initially on marketing attribution and revenue forecasting. The stack is Python-heavy (NumPy, SciPy, pandas) with production infrastructure (Kubernetes, Terraform, PostgreSQL, Elasticsearch) and multi-cloud deployment (AWS, GCP, Azure), indicating a mature, data-intensive system. Active hiring is entirely senior-level engineering and research roles, paired with projects on production causal systems, real-time analytics infrastructure, and IP protection—suggesting a transition from research-to-product stage with emphasis on statistical rigor and competitive moat-building.
Tech Stack 53 technologies
Core StackPython Node.js JavaScript TypeScript React PostgreSQL Elasticsearch AWS Docker Kubernetes Terraform pandas Apache NiFi Cursor Pandas NumPy Iceberg GCP Azure CI/CD SQLAlchemy Pydantic Bash Poetry Linear Numba SciPy OpenAPI Sphinx MkDocs+20 more
What Alembic Technologies Is Building
◆Challenges
- Scaling platform reliability
- Proving value of data cloud ai solutions
- Measurement challenges
- Statistical rigor at enterprise scale
- Data-intensive systems
- Enhancing observability
- Protecting proprietary technology
- Managing global ip portfolio
- Improving observability
- Scaling gpu-resident compute
▲Active Projects
- Monitoring and incident response processes
- Field studies
- Research implementations
- Build production systems for causal inference
- Design novel approaches to marketing measurement problems
- Create tools and libraries for advanced analytics
- Scalable infrastructure for real-time analytics and ml workloads
- Ci/cd pipeline evolution
- Code-level ip harvesting
- Build the causal moat
Hiring Activity
6 roles · 2 in 30d
Department
Seniority
Company intelligence
