Ehtasham F.

I build production AI systems — RAG assistants, LLM agents and AI-powered trading tools — engineered in Rust and Python so they stay fast, accurate and affordable once real users arrive. ⭐ Rust & Solana engineer · 1,000+ hours on Upwork · my 4 most recent reviewed contracts are all 5.0 Most AI projects look great in a demo and fall apart in production: slow answers, made-up facts, agents that loop, API bills that explode. My job is the engineering that fixes that — proper retrieval, evaluations, guardrails, caching and monitoring. ━━━━━━━━━━━━━━━━━━━━ 🤖 𝗔𝗜 & 𝗟𝗟𝗠 𝗦𝗬𝗦𝗧𝗘𝗠𝗦 ━━━━━━━━━━━━━━━━━━━━ ▸ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀: RAG over your docs, tickets, PDFs or codebase, with hybrid search, source citations and accuracy tests. ▸ 𝗔𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝘁𝗮𝗸𝗲 𝗮𝗰𝘁𝗶𝗼𝗻: AI agents that call your APIs, use tools via MCP and run multi-step workflows with limits and human approval. ▸ 𝗔𝗜 𝗶𝗻𝘀𝗶𝗱𝗲 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁: chat, smart search, summarization and classification, with streaming and cost control. ▸ 𝗔𝗜 𝗳𝗼𝗿 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 & 𝗰𝗿𝘆𝗽𝘁𝗼: research and signal agents, AI trading assistants, and on-chain agents on Solana with spending limits. ━━━━━━━━━━━━━━━━━━━━ ⚙️ 𝗥𝗨𝗦𝗧, 𝗧𝗥𝗔𝗗𝗜𝗡𝗚 & 𝗦𝗢𝗟𝗔𝗡𝗔 ━━━━━━━━━━━━━━━━━━━━ ▸ 𝗧𝗿𝗮𝗱𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀: execution engines, order books, price feeds, Jupiter/Raydium/Jito integrations. ▸ 𝗦𝗼𝗹𝗮𝗻𝗮 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝘀: Rust/Anchor tokens, staking, vesting, escrow, launchpads, and fixes for broken programs. ▸ 𝗙𝗮𝘀𝘁 𝗯𝗮𝗰𝗸𝗲𝗻𝗱𝘀: high-performance Rust APIs and services when Python or Node is too slow. ━━━━━━━━━━━━━━━━━━━━ 🏆 𝗣𝗥𝗢𝗢𝗙 (source code and benchmarks in my portfolio) ━━━━━━━━━━━━━━━━━━━━ ✅ RAG & vector search engine built from scratch in Rust: hybrid HNSW + keyword retrieval, 99.6% recall at 39K queries/sec. ✅ GPT-style language model trained and served in Rust behind an OpenAI-compatible API. ✅ Order matching engine in Rust: 4.4M orders/sec with deterministic results. ✅ Client work: a complex crypto trading execution system. The client wrote that I "went above and beyond to make sure we had a first-rate product." ━━━━━━━━━━━━━━━━━━━━ 🤝 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 ━━━━━━━━━━━━━━━━━━━━ 𝟭. Free 20-minute call, or a written review of your idea within 24 hours. 𝟮. A short plan with fixed milestones, so you know the cost and dates up front. 𝟯. A working demo early, then iterate. AI features ship with an evaluation set, so quality is measured, not guessed. 𝟰. Clean handover: code, README, deployment steps, and 30 days of free bug fixes. ━━━━━━━━━━━━━━━━━━━━ 🛠 𝗦𝗧𝗔𝗖𝗞 ━━━━━━━━━━━━━━━━━━━━ AI: OpenAI, Claude, LangChain, LangGraph, LlamaIndex, MCP, Qdrant, pgvector, Hugging Face Engineering: Rust (Tokio, Axum), Python (FastAPI), TypeScript, Next.js, PostgreSQL, Redis, Docker Web3: Solana, Anchor, Jupiter, Jito, Solidity 👉 Tell me what you want the AI to do and where your data lives. I'll reply with an approach, timeline and fixed quote.