Senior Full-Stack / Platform Engineer
Frontend · Backend · Data Systems · DevOps · Kubernetes · Automation · Rust · Python · Rails · TypeScript
I build complete software systems end-to-end: frontend applications, backend services, APIs, databases, infrastructure, deployment workflows, monitoring, automation, and data pipelines.
My strongest work is in complex, data-heavy products where the system needs to be reliable, inspectable, performant, and operationally useful. I work across product interfaces, backend architecture, data modeling, infrastructure, DevOps, system administration, performance optimization, monitoring, and internal tooling.
I have built SaaS products, market research platforms, trading infrastructure, research systems, dashboards, data pipelines, automation tools, browser extensions, CLIs, and backend platforms.
Previously built automated trading infrastructure for a hedge fund, including large-scale strategy backtesting, analytics, automated strategy selection, dashboards, and cloud operations. Current work includes QuantBox: a Rust/Python systems platform for research infrastructure, simulation, market-data ingestion, runtime systems, and automation.
I built an internal futures trading workstation for managing multiple funded-style accounts from one operator surface. The system combined execution, copy trading, risk controls, account fan-out, strategy dispatch, live state monitoring, and research workflows.
Key capabilities:
- Managed 10 accounts simultaneously from a single execution and monitoring UI
- Copy-traded orders across account groups with per-account position, balance, drawdown, and guardrail visibility
- Ran hundreds of strategy variants across live and replay workflows
- Backtested thousands of strategy/day/configuration combinations with sortable strategy comparison views
- Supported real-time backtesting, live dispatch review, account health checks, kill switches, flatten/cancel controls, and operator explanations for each action
Rust-first research, simulation, runtime, and evidence platform for systematic trading.
What it demonstrates:
- Systems architecture
- Rust/Python engineering
- Simulation and evaluation
- Data ingestion and replay
- Runtime infrastructure
- Risk and drawdown logic
- Evidence capture
- Operational tooling
ClickHouse-backed cryptocurrency strategy backtester using SQL-native vectorized execution.
What it demonstrates:
- Data modeling
- ClickHouse analytics
- Query optimization
- High-volume backtesting
- SQL-native research workflows
- Performance-oriented system design
CLI toolkit for wallet alerts, replayable market analysis, SQLite storage, and trader profile intelligence.
What it demonstrates:
- CLI product design
- Data extraction and normalization
- SQLite-backed local workflows
- Replayable event storage
- User-facing automation tools
Explainable event-matching system for cross-platform prediction-market analysis.
What it demonstrates:
- Event matching
- Data normalization
- Explainable algorithms
- Cross-platform data modeling
- Research tooling
Built complete product interfaces, dashboards, admin tools, browser extensions, and customer-facing workflows across SaaS, analytics, automation, and internal operations products.
What it demonstrates:
- Full-stack product development
- TypeScript/React interfaces
- Dashboards and admin tools
- Browser extensions
- UX for complex data workflows
- API integration
- Full-stack product development
- Frontend application development
- Backend architecture
- API design
- Data modeling and database design
- Query optimization and performance tuning
- DevOps and system administration
- Kubernetes, Docker, Linux, AWS
- CI/CD and deployment automation
- Monitoring, observability, Grafana dashboards
- SaaS products and internal platforms
- Rails/PostgreSQL application development
- Rust/Python systems engineering
- Market-data and research infrastructure
- Automation and AI-assisted workflows
Languages: Rust, Python, Ruby, Go, TypeScript, SQL
Frontend: React, TypeScript, HTML, CSS, dashboards, browser extensions, admin tools
Backend: Ruby on Rails, FastAPI, APIs, WebSockets, background jobs, service architecture, CLI systems
Data: PostgreSQL, ClickHouse, SQLite, ETL, data modeling, event logs, analytics pipelines
Infrastructure: Kubernetes, Docker, AWS, Linux, Ansible, CI/CD, sysadmin, Grafana, monitoring
Domains: SaaS, internal tools, automation, analytics, research infrastructure, trading systems, data-heavy products
- Email: bijan.pourriahi@gmail.com