Senior Full-Stack / Platform Engineer
Data Pipelines · Automation Infrastructure · Browser Automation · DevOps · Rust · Python · Rails · TypeScript

I build complete software systems end-to-end: product interfaces, backend services, APIs, databases, data pipelines, orchestration systems, deployment workflows, monitoring, automation, and internal tooling.

My strongest work is in complex, data-heavy products where reliability, observability, performance, and operational usefulness matter. I’m comfortable working across frontend, backend architecture, data modeling, Linux infrastructure, DevOps, production debugging, performance optimization, and systems automation.

I have built SaaS products, market research platforms, trading infrastructure, research systems, dashboards, browser automation platforms, browser extensions, CLIs, and backend services.

Relevant work includes high-volume browser automation infrastructure, proxy/session management, account/session isolation, provider access routing, Dockerized workers, job orchestration, retries, logging, failure recovery, monitoring, and operational reliability.

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