Ali H.

(𝗘𝗾𝘂𝗶𝘁𝗶𝗲𝘀, 𝗢𝗽𝘁𝗶𝗼𝗻𝘀, 𝗙𝘂𝘁𝘂𝗿𝗲𝘀, 𝗖𝗿𝘆𝗽𝘁𝗼,𝗙𝗼𝗿𝗲𝘅, 𝗦𝘁𝗼𝗰𝗸𝘀) 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: (Alpaca, Interactive Brokers, Thinkorswim, QuantConnect, NinjaTrader, MT4/5, Binance,Bybit, Blufin, Quantower) or Custom Backtesting Engines, CFD development, Custom Trading Systems or Trading Infra. 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱: Senior Software Engineer and Algo trader designing institutional-grade, execution-ready trading systems for hedge funds, proprietary trading desks, and advanced fintech teams. ✅ Over $1.5 million under mangement. ✅ 70k+ Traders community. ✅ 20+ happy clients. I specialize in turning robust alpha hypotheses into live, low-latency trading engines with proper risk, monitoring, and fail-safes built in from day one. From high-frequency execution to liquidity-providing market-making, I build systems that are latency-aware, resilient under stress, and designed for real capital, not just attractive backtests. 𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱 Trading bots integration with with brokerage accounts, creating dashboards for them, deploying them into the cloud, and related financial automation jobs to include copy-trading, back-testing, alerts, TradingView webhooks, order forms, order routing scripts, sentiment analysis (like on r/WallStreetBets), scanners/screeners, as well as web scrapers Statistical arbitrage and market-making strategies: spread modeling, co-integration, pairs and baskets, inventory and quote-risk controls, and continuous PnL/risk monitoring. Trading aggregators and smart order routing: multi-exchange connectivity, routing logic, internal crossing, venue selection, slippage control, and real-time risk/hard-limits. ML and LLM-augmented research pipelines: feature engineering for non-stationary series, signal stability testing, reinforcement-learning style policy evaluation, and sentiment/NLP inputs where they add real edge. Crypto and DeFi execution: CEX/DEX arbitrage, AMM routing, perpetual swaps, and integrations across on-chain protocols and off-chain venues. Low-latency & backend: C++, C#, Rust, Python, with practical experience building production trading and automation tools and server-side components. 𝗧𝗵𝗲 𝗲𝗻𝗱 𝗴𝗼𝗮𝗹 𝗶𝘀 𝗮𝗹𝘄𝗮𝘆𝘀 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲: 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗯𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱, 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗲𝗱, 𝗮𝗻𝗱 𝗶𝘁𝗲𝗿𝗮𝘁𝗲𝗱 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗶𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗯𝗮𝗰𝗸𝘁𝗲𝘀𝘁 𝗰𝗵𝗮𝗿𝘁𝘀. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗼𝗿 𝘂𝗽𝗴𝗿𝗮𝗱𝗶𝗻𝗴 𝗮 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 𝘀𝘁𝗮𝗰𝗸? 𝗦𝗵𝗮𝗿𝗲 𝘆𝗼𝘂𝗿 𝘀𝗲𝘁𝘂𝗽, 𝘃𝗲𝗻𝘂𝗲𝘀, 𝗮𝗻𝗱 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀, 𝗮𝗻𝗱 𝘄𝗲 𝗰𝗮𝗻 𝗺𝗮𝗽 𝗼𝘂𝘁 𝗮 𝗰𝗼𝗻𝗰𝗿𝗲𝘁𝗲 𝗽𝗹𝗮𝗻.