Hire the Best Distributed Systems Engineers

📌 𝙄𝙛 𝙮𝙤𝙪 𝙬𝙖𝙣𝙣𝙖 𝙙𝙤 𝙨𝙤𝙢𝙚𝙩𝙝𝙞𝙣𝙜 𝘼𝙧𝙤𝙪𝙣𝙙 𝘼𝙄 𝙤𝙧 𝙞𝙣𝙛𝙧𝙖𝙨𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚 - 𝙏𝙝𝙚𝙧𝙚 𝙖𝙧𝙚 10 𝙨𝙩𝙚𝙥𝙨: 🔹𝙎𝙩𝙚𝙥 1 ▪︎ 𝙃𝙞𝙧𝙚 𝙢𝙚, 𝙖𝙣𝙙 𝙞 𝙬𝙞𝙡𝙡 𝙙𝙤 𝙧𝙚𝙢𝙖𝙞𝙣𝙞𝙣𝙜 9 𝙛𝙤𝙧 𝙮𝙤𝙪. Hello, I am 𝗖𝗵𝗼𝘂𝗱𝗵𝗿𝘆. I wrote the 𝗜𝗮𝗖 for (𝗠𝗶𝗱𝗱𝗹𝗲 𝗘𝗮𝘀𝘁'𝘀 #𝟭 𝘀𝘂𝗽𝗲𝗿𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿) GPU cluster orchestration on 𝗞𝗔𝗨𝗦𝗧 𝗦𝗵𝗮𝗵𝗲𝗲𝗻 𝗜𝗜𝗜, the 𝗠𝗶𝗱𝗱𝗹𝗲 𝗘𝗮𝘀𝘁'𝘀 #𝟭 𝘀𝘂𝗽𝗲𝗿𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿 (𝗿𝗮𝗻𝗸𝗲𝗱 𝟭𝟴𝘁𝗵 globally on the Nov 2025 TOP500, 2,800 NVIDIA GH200 Grace Hoppers, liquid-cooled HPE Cray EX). That's the level of GPU and 𝗟𝗟𝗠 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 I work on, 𝗼𝗻-𝗽𝗿𝗲𝗺 and in the 𝗰𝗹𝗼𝘂𝗱. 📌 What I'm an expert in: 🔹𝗦𝗲𝗹𝗳-𝗵𝗼𝘀𝘁𝗲𝗱 & 𝗹𝗼𝗰𝗮𝗹 𝗟𝗟𝗠 𝘀𝗲𝗿𝘃𝗶𝗻𝗴 (𝘃𝗟𝗟𝗠, 𝗡𝗩𝗜𝗗𝗜𝗔 𝗧𝗿𝗶𝘁𝗼𝗻, 𝗧𝗲𝗻𝘀𝗼𝗿𝗥𝗧, 𝗦𝗚𝗟𝗮𝗻𝗴) 🔹𝗚𝗣𝗨 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (𝗙𝗣𝟴/𝗜𝗡𝗧𝟴 𝗾𝘂𝗮𝗻𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗙𝗹𝗮𝘀𝗵𝗔𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻, 𝘁𝗲𝗻𝘀𝗼𝗿 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹𝗶𝘀𝗺, 𝗠𝗜𝗚 𝗼𝗻 𝗛𝟭𝟬𝟬/𝗔𝟭𝟬𝟬/𝗚𝗛𝟮𝟬𝟬/𝗕𝗹𝗮𝗰𝗸𝘄𝗲𝗹𝗹) 🔹𝗟𝗟𝗠 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴 & 𝗰𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (𝗟𝗼𝗥𝗔, 𝗣𝗘𝗙𝗧, 𝗨𝗻𝘀𝗹𝗼𝘁𝗵, 𝗱𝗼𝗺𝗮𝗶𝗻 𝗮𝗱𝗮𝗽𝘁𝗮𝘁𝗶𝗼𝗻) 🔹𝗕𝗮𝗿𝗲-𝗺𝗲𝘁𝗮𝗹 𝗚𝗣𝗨 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 (𝗣𝗿𝗼𝘅𝗺𝗼𝘅, 𝗥𝗮𝗻𝗰𝗵𝗲𝗿, 𝗞𝟯𝘀, 𝗢𝗽𝗲𝗻𝗦𝗵𝗶𝗳𝘁, 𝗖𝗮𝗹𝗶𝗰𝗼, 𝗠𝗲𝘁𝗮𝗹𝗟𝗕, 𝗛𝗔𝗣𝗿𝗼𝘅𝘆) 🔹𝗠𝗮𝗻𝗮𝗴𝗲𝗱 𝗰𝗹𝗼𝘂𝗱 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝘄𝗶𝘁𝗵 𝗚𝗣𝗨 (𝗚𝗞𝗘, 𝗘𝗞𝗦, 𝗔𝗞𝗦, 𝗩𝗲𝗿𝘁𝗲𝘅 𝗔𝗜, 𝗦𝗮𝗴𝗲𝗠𝗮𝗸𝗲𝗿, 𝗖𝗹𝗼𝘂𝗱 𝗥𝘂𝗻) 🔹𝗡𝗩𝗜𝗗𝗜𝗔 𝗚𝗣𝗨 𝗢𝗽𝗲𝗿𝗮𝘁𝗼𝗿, 𝗞𝘂𝗯𝗲𝗳𝗹𝗼𝘄, 𝗥𝗮𝘆, 𝗧𝗿𝗶𝘁𝗼𝗻 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗦𝗲𝗿𝘃𝗲𝗿, 𝗰𝘂𝘀𝘁𝗼𝗺 𝗞𝟴𝘀 𝗼𝗽𝗲𝗿𝗮𝘁𝗼𝗿𝘀 (𝗜 𝗯𝘂𝗶𝗹𝘁 𝗩𝗥𝗔𝗠 𝗚𝗣𝗨 𝗢𝗽𝗲𝗿𝗮𝘁𝗼𝗿 + 𝗔𝗹𝗶𝘆𝘂𝗻 𝗚𝗣𝗨 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 𝗳𝗼𝗿 𝗞𝘂𝗯𝗲𝗳𝗹𝗼𝘄) 🔹𝗣𝗿𝗶𝘃𝗮𝘁𝗲 & 𝗼𝗻-𝗽𝗿𝗲𝗺 𝗟𝗟𝗠 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀 (𝗛𝗜𝗣𝗔𝗔, 𝗚𝗗𝗣𝗥, 𝗮𝗶𝗿-𝗴𝗮𝗽𝗽𝗲𝗱, 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗲𝗱 𝘁𝗲𝗮𝗺𝘀) 🔹𝗛𝗲𝘁𝗲𝗿𝗼𝗴𝗲𝗻𝗲𝗼𝘂𝘀 𝗛𝗣𝗖 & 𝗔𝗜 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (𝗚𝗣𝗨, 𝗙𝗣𝗚𝗔, 𝗔𝗦𝗜𝗖, 𝗫𝗣𝗨, 𝗺𝘂𝗹𝘁𝗶-𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴) 🔹𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 & 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 (𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗖𝗿𝗲𝘄𝗔𝗜, 𝗖𝗹𝗮𝘂𝗱𝗲 𝗔𝗴𝗲𝗻𝘁 𝗦𝗗𝗞, 𝗠𝗖𝗣 𝘀𝗲𝗿𝘃𝗲𝗿𝘀) 🔹𝗩𝗼𝗶𝗰𝗲 𝗮𝗴𝗲𝗻𝘁 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (𝗥𝗲𝘁𝗲𝗹𝗹 𝗔𝗜, 𝗩𝗮𝗽𝗶, 𝗧𝘄𝗶𝗹𝗶𝗼, 𝗘𝗹𝗲𝘃𝗲𝗻𝗟𝗮𝗯𝘀, 𝗻𝟴𝗻, 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀) 🔹𝗥𝗔𝗚 & 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗗𝗼𝗰𝗹𝗶𝗻𝗴, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚, 𝗽𝗴𝘃𝗲𝗰𝘁𝗼𝗿, 𝗙𝗔𝗜𝗦𝗦, 𝗣𝗶𝗻𝗲𝗰𝗼𝗻𝗲, 𝗤𝗱𝗿𝗮𝗻𝘁, 𝗖𝗵𝗿𝗼𝗺𝗮𝗗𝗕) 🔹𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲-𝗮𝘀-𝗰𝗼𝗱𝗲 (𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺, 𝗔𝗻𝘀𝗶𝗯𝗹𝗲, 𝗣𝘂𝗹𝘂𝗺𝗶, 𝗖𝗿𝗼𝘀𝘀𝗽𝗹𝗮𝗻𝗲, 𝗛𝗲𝗹𝗺) 🔹𝗖𝗜/𝗖𝗗 𝗳𝗼𝗿 𝗠𝗟/𝗔𝗜 (𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀, 𝗚𝗶𝘁𝗟𝗮𝗯 𝗖𝗜, 𝗝𝗲𝗻𝗸𝗶𝗻𝘀, 𝗖𝗶𝗿𝗰𝗹𝗲𝗖𝗜, 𝗔𝗿𝗴𝗼𝗖𝗗, 𝗙𝗹𝘂𝘅) 🔹𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗳𝗼𝗿 𝗔𝗜 𝘄𝗼𝗿𝗸𝗹𝗼𝗮𝗱𝘀 (𝗣𝗿𝗼𝗺𝗲𝘁𝗵𝗲𝘂𝘀, 𝗚𝗿𝗮𝗳𝗮𝗻𝗮, 𝗟𝗼𝗸𝗶, 𝗗𝗮𝘁𝗮𝗱𝗼𝗴, 𝗢𝗽𝗲𝗻𝗧𝗲𝗹𝗲𝗺𝗲𝘁𝗿𝘆) 🔹𝗖𝗹𝗼𝘂𝗱 𝘀𝗽𝗲𝗻𝗱 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗔𝗜 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 📌 Real results, defensible on a call: 🔹𝗖𝘂𝘁 𝘃𝗟𝗟𝗠 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗹𝗮𝘁𝗲𝗻𝗰𝘆 𝗳𝗿𝗼𝗺 𝟯.𝟮𝘀 𝘁𝗼 𝟴𝟬𝟬𝗺𝘀 𝗮𝘁 𝗮 𝗨𝗦 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 🔹𝗗𝗿𝗼𝗽𝗽𝗲𝗱 𝘁𝗵𝗲𝗶𝗿 𝗺𝗼𝗻𝘁𝗵𝗹𝘆 𝗰𝗹𝗼𝘂𝗱 𝗯𝗶𝗹𝗹 𝗳𝗿𝗼𝗺 $𝟭𝟬𝗞 𝘁𝗼 $𝟰𝗞 🔹𝗦𝗲𝗿𝘃𝗲𝗱 𝗟𝗟𝗠𝘀 𝘁𝗼 𝟭,𝟬𝟬𝟬+ 𝗰𝗼𝗻𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝘂𝘀𝗲𝗿𝘀 𝗼𝗻 𝗯𝗮𝗿𝗲-𝗺𝗲𝘁𝗮𝗹 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀, 𝘇𝗲𝗿𝗼 𝘂𝗻𝗽𝗹𝗮𝗻𝗻𝗲𝗱 𝗱𝗼𝘄𝗻𝘁𝗶𝗺𝗲 𝗳𝗼𝗿 𝟭𝟮 𝗺𝗼𝗻𝘁𝗵𝘀 🔹𝗦𝗵𝗶𝗽𝗽𝗲𝗱 𝘁𝗵𝗲 𝗗𝗼𝗰𝗹𝗶𝗻𝗴 + 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗳𝗼𝗿 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹 𝗿𝗲𝗮𝗹 𝗲𝘀𝘁𝗮𝘁𝗲 𝗹𝗲𝗮𝘀𝗲 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗮𝘁 𝗡𝗲𝘀𝘁𝗯𝗼𝘅 𝗔𝗜, 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱 𝗼𝗻 𝗚𝗖𝗣 𝘄𝗶𝘁𝗵 𝗮 𝗵𝘂𝗺𝗮𝗻 𝗿𝗲𝘃𝗶𝗲𝘄 𝗾𝘂𝗲𝘂𝗲 📌 What clients say: "𝘴𝘪𝘯𝘨𝘭𝘦-𝘩𝘢𝘯𝘥𝘦𝘥𝘭𝘺 𝘣𝘶𝘪𝘭𝘵 𝘰𝘶𝘳 𝘒𝘶𝘣𝘦𝘳𝘯𝘦𝘵𝘦𝘴 𝘪𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘧𝘰𝘳 𝘰𝘶𝘳 𝘎𝘗𝘜 𝘴𝘦𝘵𝘶𝘱" "𝘢 𝘧𝘶𝘭𝘭 𝘴𝘵𝘢𝘤𝘬 𝘈𝘐 𝘨𝘶𝘺" "𝘦𝘯𝘦𝘳𝘨𝘦𝘵𝘪𝘤, 𝘩𝘶𝘯𝘨𝘳𝘺, 𝘢𝘯𝘥 𝘴𝘩𝘢𝘳𝘱" "𝘨𝘦𝘵𝘴 𝘤𝘰𝘯𝘤𝘦𝘱𝘵𝘴 𝘲𝘶𝘪𝘤𝘬𝘭𝘺 𝘢𝘯𝘥 𝘪𝘴 𝘢𝘯 𝘪𝘯𝘤𝘳𝘦𝘥𝘪𝘣𝘭𝘺 𝘩𝘢𝘳𝘥 𝘸𝘰𝘳𝘬𝘦𝘳" "𝘸𝘩𝘦𝘯 𝘩𝘦 𝘴𝘢𝘺𝘴 𝘩𝘦'𝘭𝘭 𝘥𝘰 𝘪𝘵 𝘣𝘺 𝘢 𝘥𝘦𝘢𝘥𝘭𝘪𝘯𝘦, 𝘩𝘦 𝘥𝘰𝘦𝘴. 𝘖𝘸𝘯𝘴 𝘢𝘤𝘤𝘰𝘶𝘯𝘵𝘢𝘣𝘪𝘭𝘪𝘵𝘺" "𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩𝘦𝘴 𝘵𝘩𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘢𝘴 𝘪𝘧 𝘪𝘵 𝘸𝘦𝘳𝘦 𝘩𝘪𝘴 𝘰𝘸𝘯" "𝘸𝘰𝘳𝘬𝘦𝘥 𝘭𝘢𝘵𝘦 𝘪𝘯𝘵𝘰 𝘵𝘩𝘦 𝘯𝘪𝘨𝘩𝘵 𝘵𝘰 𝘨𝘦𝘵 𝘪𝘵 𝘥𝘰𝘯𝘦" "𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘦𝘥 𝘸𝘩𝘢𝘵 𝘩𝘦 𝘱𝘳𝘰𝘮𝘪𝘴𝘦𝘥 𝘢𝘯𝘥 𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘥 𝘤𝘭𝘦𝘢𝘳 𝘥𝘰𝘤𝘶𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯" "𝘪𝘯𝘤𝘳𝘦𝘥𝘪𝘣𝘭𝘺 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘵, 𝘢𝘥𝘥𝘳𝘦𝘴𝘴𝘦𝘥 𝘦𝘷𝘦𝘳𝘺 𝘤𝘰𝘯𝘤𝘦𝘳𝘯 𝘪𝘯 30 𝘮𝘪𝘯𝘶𝘵𝘦𝘴" "𝘢 𝘴𝘢𝘧𝘦 𝘣𝘦𝘵" A bit about me: I'm Acting CTO at Peregrine Ventures AI, currently building a product called Deplexify. I also run a dual RTX Pro 6000 Blackwell server at home (EPYC, Proxmox, GPU passthrough), so on-prem GPU work isn't a side skill. It's my daily reality.

Backend engineer for AI infrastructure and developer experience. Primary in Go and Python, with TypeScript and Rust where the work demands it. I ship small, focused, self-contained software: one binary, one config, one deploy. What I build: ** Compilers and language tooling: Author of Kilnx, an htmx-native backend language. Full compiler pipeline in Go (~19K LOC): lexer, recursive-descent parser, static type system with SQL-aware type inference, security analyzer, query optimizer, LSP server, embedded SQLite runtime, RBAC, WebSockets. Single ~15MB binary output, Apache 2.0. **Data quality and pipelines: Author of Provero, a declarative data quality engine on PyPI. Multi-dialect SQL (PostgreSQL, DuckDB, SQLite), 16 check types, SodaCL import, dbt test export. Built for data engineers, not data scientists. **Developer tooling at scale: Maintainer of AToolZ, a 47-repo collective: distributed via Homebrew, PyPI, VS Code Marketplace, and Chrome Web Store. Flagships include htmx-devtools, htmx-vscode-toolkit (IntelliSense across 20+ template languages), picocrawl (URL to LLM-ready Markdown, CLI + HTTP + MCP in one 15MB binary), terraxi (cloud discovery to Terraform/OpenTofu codegen), and scope-guard (Claude Code plugin detecting agent scope drift). **AI agent infrastructure: MCP servers (flyte-mcp exposes Flyte V2 to AI coding assistants), LSP servers (kitty-lsp-toolkit), Claude Code plugins, agentic knowledge bases (oss-kb for LLM code review with historical context). OSS contributor in Apache Airflow, Backstage, Burr, Flyte, Jenkins, htmx, and _hyperscript. I read source before opening issues, ship small PRs, and document trade-offs. Production track record: - Financial transaction pipeline: Go service processing 2M+ daily transactions. Custom query optimizer cut p99 latency 60%. Cutover from nightly batch to streaming on bare metal, zero downtime. - Industrial IoT telemetry: 50K events/s sustained from 500+ field devices. PostgreSQL time-series storage, custom connection pooling. - Document processing: 100K+ documents/day with OCR, classification, structured extraction. Kubernetes workers autoscale on queue depth. - Real-time analytics: aggregation engine took dashboard queries from 12s to 180ms. Postgres materialized views, Redis pub/sub. - ERP migration (retail): 8M+ records to a modern stack. Diff engine and dry-run mode cut migration from 3 days to 6 hours. - Multi-tenant API (manufacturing): 40+ tenants, p99 90ms at 3K QPS. Row-level RBAC, PostgreSQL logical replication. Industries: finance, energy, oil and gas, retail, manufacturing. Cross-border delivery US, Brazil, LATAM. Bilingual Portuguese, full professional English. How I work: - I read the codebase before proposing a fix. - I write tests when they prevent regression, not for theater. - I document trade-offs in PR descriptions and design docs. - I prefer single-binary, single-config deploys over service sprawl. - I refuse work where the scope or constraints are not defined. Stack: Go, Python, TypeScript, Rust, SQL. PostgreSQL, SQLite, DuckDB, Redis. Kubernetes, Docker, bare-metal Linux, AWS, GitHub Actions, Apache Airflow. LSP, MCP, compiler design, static type systems. Best fit engagements: - Backend service design, migration, or rewrite (Go or Python). - Data quality, pipelines, and observability. - Developer tooling: LSPs, MCP servers, CLIs, VS Code extensions, Chrome DevTools panels. - AI agent infrastructure: scope enforcement, knowledge bases, MCP integrations. - Compiler design and DSL implementation. Reach me here on Upwork or at andre@aex.partners.

The engineer you call when software, infrastructure, and networking all need to work together. 🚀 Senior DevOps Engineer | Backend Developer | Cloud & Platform Engineer Most technical problems don't exist in a single layer. An application is slow, but the root cause is the database. A deployment fails because of infrastructure. An API works locally but breaks in production because of networking. AI features underperform because the data pipeline was designed incorrectly. My background spans software development, cloud infrastructure, Linux systems, networking, automation, and AI integrations, allowing me to build and troubleshoot systems end-to-end. Over the last 5+ years, I have worked across AWS, GCP, Kubernetes, Docker, Terraform, CI/CD automation, backend APIs, distributed systems, AI-powered applications, and production environments supporting real business operations. 🎯 What I Can Help With ✅ Backend Development (Node.js, Python, Go, .NET) ✅ Cloud Infrastructure (AWS, GCP) ✅ Infrastructure as Code (Terraform) ✅ Kubernetes & Docker Platforms ✅ CI/CD Automation (GitHub Actions, GitLab CI, Jenkins) ✅ Linux Administration & Troubleshooting ✅ Database Design & Optimization ✅ AI & LLM Integrations (OpenAI, RAG, AI Agents) ✅ Monitoring, Observability & Reliability Engineering ✅ Performance Optimization & Cloud Cost Reduction 🔧 Clients Typically Bring Me In For • Building platforms that require both development and infrastructure expertise • Solving production issues that span applications, databases, networking, and cloud services • Modernizing deployment workflows and DevOps practices • Designing scalable cloud-native architectures • Integrating AI capabilities into existing products • Reducing operational complexity and cloud costs 💻 Core Technologies ☁️ Cloud AWS • GCP • Azure ⚙️ Infrastructure Terraform • Docker • Kubernetes • ECS • EKS • Linux 🖥 Backend Node.js • Python • Go • .NET • FastAPI 🌐 Frontend Next.js • React • TypeScript 🗄 Databases PostgreSQL • MySQL • MongoDB • Redis 🚀 DevOps GitHub Actions • GitLab CI • Jenkins • Monitoring • Observability 🤖 AI OpenAI • LLM Integrations • RAG Systems • AI Agents 💡 I work best with startups, SaaS companies, and engineering teams that need a single engineer capable of owning systems end-to-end—from architecture and development to deployment and operations. 🟢 If your project involves software, infrastructure, automation, or AI, let's talk.

I am an ACM-ICPC World Finalist and software engineer. I have been developing backend and DevOps solutions using C++, Java, and Python since 2016. I have experience in multiple domains that include fintech, agrotech, health tech, IoT, and Saas. I have been working as a remote developer with globally distributed teams since 2019. I am a quick learner, good with communication, proactive and punctual human being. Nothing excites more me than a challenge that is necessary but difficult to solve. I am also a competitive programmer and expert in data structures and algorithms. I have a decent understanding of UNIX systems especially how different types of data structures are blended to solve complex problems of operating systems. I am a team player and can work as solo as well. I never compromise the quality of my work doesn't matter how the pressure is. And, I believe in requirement analysis as the most crucial part of engagement.

I design software systems that scale reliably under real-world production load. My work focuses on implementation-ready system design, comprehensive infrastructure definitions, performance validation, and observability combined with control frameworks that help keep systems stable. I am a graduate of IIT Madras, and I specialize in designing production-grade platforms for data, machine learning, and distributed applications. My work focuses on three areas: 1. System Architecture : implementation-ready designs, infrastructure definitions (Terraform), and clear API contracts. 2. Performance Validation : realistic load testing to identify scaling limits and recovery behavior before production. 3. Observability & Control : runtime monitoring, controlled rollouts, event replay, and operational reporting. Technologies: Python, distributed systems, machine learning systems, cloud infrastructure, Terraform, APIs.

23+ years in Linux/Windows administration, DevOps, and cloud infrastructure. I build, secure, and scale production systems 24/7 — for MSP clients and direct engagements across industries. If your server is down, your deployment is failing, or you need infrastructure built right the first time — I'm the engineer you call. ━━ SERVER & SYSTEMS ━━ Linux (CentOS, Debian, Ubuntu, Amazon Linux, Rocky Linux) and Windows Server (2012–2025). Active Directory, Group Policy, Intune, hybrid identity. Nginx, Apache, Sendmail, Qmail, Postfix, Exim — MTA setup, Dovecot, SpamAssassin, OpenDKIM, SPF/DKIM/DMARC. Veeam, Acronis, cloud-native DR. Hypervisors: KVM, VMware ESXi, Hyper-V, Proxmox VE — HA clusters, live migration, Ceph/ZFS, Proxmox Backup Server. Redis, Varnish. QNAP NAS — storage management, Plex Media Server deployment, VPN tunnel integration. WHM/cPanel, Plesk, Virtualmin, CloudPanel, CyberPanel. ━━ CLOUD INFRASTRUCTURE ━━ AWS: EC2, ECS, EKS, RDS, S3, Route 53, IAM, VPC, CloudWatch, Lambda, API Gateway, Elastic Disaster Recovery. GCP: Cloud Run, Cloud Build, Firestore, GKE, IAM, VPC, Pub/Sub, Cloud Storage, Secret Manager, Cloud Monitoring. Cloudflare (WAF, Workers, Zero Trust, CDN). DigitalOcean, Hetzner, Vultr. MinIO: S3-compatible object storage on bare metal, VMs, Kubernetes — distributed mode, SSE-S3/KMS, lifecycle policies, drop-in S3 for backups and MLOps. Railway: Full-stack PaaS — GitHub/Docker auto-build, managed DBs (PostgreSQL, MySQL, Redis), private networking, env variables, cron workers, auto-scaling. ━━ SECRETS MANAGEMENT ━━ HashiCorp Vault: Dynamic secrets for AWS IAM, databases, cloud providers — TTL-bound credentials, auto-revoke. PKI for internal CA and on-demand TLS. Vault Secrets Operator for Kubernetes (etcd-free pod injection). Raft HA, RBAC, audit logging, Shamir unseal. Transit engine for encryption-as-a-service. CI/CD integration to eliminate hardcoded credentials. ━━ DEVOPS & CI/CD ━━ Docker, Kubernetes (EKS + self-managed: kubeadm, k3s, RKE2), Helm, Kamal. GitHub Actions, GitLab CI, Bitbucket Pipelines. Terraform, Ansible. ArgoCD, Flux (GitOps). Prometheus, Grafana, Datadog. Traefik: Cloud-native ingress — auto TLS, Docker/K8s service discovery, ForwardAuth, rate limiting, canary routing. Caddy: Zero-config-TLS reverse proxy — automatic HTTPS, on-demand certs. Preferred for self-hosted stacks. ━━ NETWORKING & SECURITY ━━ WireGuard, OpenVPN (MFA/ZTNA), IPSec/Libreswan, Xray/REALITY. Tailscale/Headscale — self-hosted mesh VPN, VPS tunnel setup, ACL policies, subnet routing. MikroTik, Juniper, SonicWall, Fortinet (FortiGate, FortiManager, FortiAnalyzer). pfSense, OPNsense. BGP, OSPF. Auth0, OAuth2, OIDC, Duo Security. LDAP/RADIUS, 802.1x, NPS/AD CS/Intune. ━━ DEVELOPMENT & AUTOMATION ━━ Python: FastAPI, Flask, Django, RESTful APIs, OpenAI API, ETL pipelines (Airbyte), orchestration (Airflow, n8n), data processing (pandas), Retool internal tools. Clean, documented, production-ready code. ━━ CONTAINERIZATION & DEPLOYMENT ━━ Docker Compose, Kubernetes manifests, Helm. Portainer, Coolify, Elestio, Traefik, Caddy. MinIO (K8s Operator/Tenant). Nextcloud, n8n, self-hosted app deployment. Vercel, Railway, Netlify, Replit. ━━ MSP & VOIP ━━ Duo Security, SpamTitan, ScreenConnect, ESET, Acronis. M365 multi-tenant administration. Asterisk and Vicidial (AWS + on-prem) — SIP trunks, IVR, call center setup, NetSIP integration. ━━ LEGACY & EARLY CAREER ━━ Foundational background in Windows desktop application development (VB, C#, Access) and web development (Core PHP, Laravel). ━━ WHAT CLIENTS HIRE ME FOR ━━ ► Emergency triage: servers down, services failing, breaches in progress ► Greenfield AWS/cloud environments built to security and compliance best practices ► CI/CD pipelines rebuilt to work reliably — no more failed deployments at 2am ► Self-hosted stacks that cut cloud bills without cutting uptime ► Kubernetes from scratch: EKS, k3s, RKE2 — setup, Helm, GitOps, day-2 operations ► HashiCorp Vault rollouts — eliminate hardcoded credentials across all pipelines ► Proxmox VE clusters: HA, live migration, Ceph storage, Proxmox Backup Server ► Network redesigns: Zero Trust, WireGuard mesh, BGP multi-homed, FortiGate, pfSense ► Ongoing managed infrastructure support and 24/7 incident response ► GCP solution design & delivery — Cloud Run, microservices, IAM, developer onboarding/offboarding ► Infrastructure, Security & Application Audits — server, network, database, cloud, and web stack ━━ INDUSTRIES SERVED ━━ SaaS · Fintech · Healthcare · E-commerce · Legal · Real Estate · Media · Education · Government · Telecoms · Startups · Enterprise. Single-server MVPs to multi-region, multi-account production environments. ━━ COMMUNICATION & PROCESS ━━ I don't disappear after the kickoff call. Clear updates at every stage, thorough documentation, and a proper handover on every engagement. Timezone-flexible. Slack, Teams, WhatsApp, Zoom, or Webex. If the work matters, it gets done right.