# Misbahuddin Mohammed > Senior Engineering Leader · AI/ML & Data Platforms · $45M+ impact · Built orgs from 3 → 22 across 3 countries · Amazon 10 yrs Location: Greater Seattle Area, United States Profile: https://flows.cv/misbahuddin I've spent 11 years at Amazon building engineering organizations and the systems they run — across logistics, supply chain, and AI/ML data platforms. The through-line: using data and automation to remove the manual, the slow, and the invisible from complex operations. Over that time I've driven $45M+ in combined cost savings and revenue impact — the accumulated result of teams I built, products I shipped, and architectural decisions that held up at scale. What I've built: On the AI/ML side — an Automated Metadata Generation platform (Claude LLM) adopted company-wide, addressing a gap where 73% of 203,000+ internal tables had no metadata. A Data Obfuscation Service processing 3,700+ monthly jobs at 99.9% availability, championed by Amazon's Privacy team as the internal benchmark. A RAG-powered conversational data catalog cutting manual curation by 500 hours/month and improving efficiency by 60%. On the logistics side — ML anomaly detection pipelines reducing NOC investigation cycles by 45%. Heimdall, a truck prioritization engine cutting vendor TAT from 6.7 to 2.2 hours across IN, AU, SG, UAE, KSA, and LATAM. Daily Freight Tracker giving real-time scheduling visibility across 100+ FCs in 6 countries. Stack: Python, TypeScript, AWS (Lambda, ECS, EKS, Kinesis, RDS), TensorFlow, PyTorch, LLM/RAG/prompt engineering. How I lead: Grew engineering orgs from 3 to 22 across India, Dubai, and Mexico. Promoted 7 engineers, conducted 150+ interviews, authored 3-year roadmaps presented to VP leadership, featured in VP Monthly Business Reviews. I believe the best engineering leaders stay close enough to the technical work to make good architectural decisions — and far enough above it to make good organizational ones. What I'm working on: Applied AI portfolio at misbahuddin.net — five Amazon-built systems re-implemented with a 20-feature LLM layer. ## Work Experience ### Senior Software Development Manager @ Amazon Jan 2022 – Present | Greater Seattle Area 🔹Successfully managed and coached underperforming employees, improving team performance and productivity. 🔹Participated in annual evaluations as a Bias Disruptor to ensure fair, unbiased assessments. 🔹Evaluated engineering contributions and presented results to leadership, securing recognition and career growth for team members. 🔹Integrated FC, Supply Chain, and Last Mile telemetry—scan events, GPS, lane latency, labor throughput, and SLA signals—into an ML anomaly detection pipeline using outlier models, isolation forests, and sequence embeddings, reducing NOC investigation cycles by 45% and defect triage by 30%. 🔹Engineered a predictive optimization framework using time-series forecasting, network flow models, and generative-AI simulators to assess surge volume, capacity constraints, and disruptions, cutting planning latency by 50% and stockout escalations by 32%. 🔹Developed a multimodal AI operations assistant using transformer models, graph embeddings, and NLP extraction of driver/associate notes, reducing triage load by 40%, improving ETA accuracy by 25%, and stabilizing cross-node reliability. 🔹Transformed an AWS QuickSight catalog into a RAG-based LLM conversational data catalog, increasing team efficiency by 60%. 🔹Engineered enhanced search across 780+ datasets by integrating metadata, lineage, feature engineering, and wiki content, boosting engagement by 40%. 🔹Built an Automated Metadata Generation System with Claude LLM and active learning, achieving 99% accuracy. 🔹Reduced manual curation by 500 hours/month through automated classification, PII tagging, and human-in-the-loop verification. 🔹Ensured GDPR and HIPAA compliance via AWS KMS encryption and a real-time logging/auditing system. 🔹Spearheaded the Research Data Lake (RDL) Catalog, saving $1.2M annually by reducing data duplication and improving discovery. ### Senior Software Development Manager @ Amazon Jan 2018 – Jan 2022 | Hyderabad, Telangana, India 🔹Led a comprehensive Native AWS Migration, transitioning to a microservices architecture with serverless computing via AWS Lambda and containerization with Amazon ECS and EKS, resulting in a 30% reduction in operational costs and enhanced scalability across multiple international sites. 🔹Developed the ISRO One-Touch BI dashboard, featuring real-time data integration with AWS Kinesis and customizable KPI widgets, achieving a 40% reduction in decision-making time and supporting critical organizational objectives such as inventory optimization and cost management. 🔹Created a Configuration Work Station with an intuitive UI and built-in validation rules, automating data input and real-time simulations, which resulted in a 50% reduction in manual errors during transportation network configuration. 🔹Built the Suraksha mobile and web application with a scalable architecture using AWS ECS and Auto Scaling, successfully managing over 107,000 COVID-19 vaccination bookings while ensuring a seamless user experience through robust data encryption and intuitive UI/UX design. 🔹Cultivated team growth by promoting 6 team members and hiring 20 engineers, contributing to an $8.8 million reduction in costs and a $34.5 million uplift in revenue through effective leadership and strategic talent acquisition. ### Manager, Web Development and Automation @ Amazon Jan 2016 – Jan 2018 | Hyderabad, Telangana, India 🔹Engineered Project Infinity real-time data pipeline using Apache Kafka, Apache Flink, and Amazon Kinesis, achieving a 70% reduction in processing latency through optimized data partitioning and in-memory caching, which enhanced live operational analytics. 🔹Developed the HEIMDALL ML-based tool for truck prioritization, integrating real-time data (GPS, traffic, inventory) and optimizing a custom ML model, resulting in a significant reduction in turn-around time from 6.7 to 2.2 hours, improving vendor experience. 🔹Implemented the Location Fraud Automation Tool (LoFAT) for Amazon Foods, targeting GPS spoofing and fake deliveries, saving $0.6 million and eliminating the need for 37 headcount hires through automated anomaly detection and real-time tracking. 🔹Created a Reactive Scheduling ML model incorporating demand forecasting and resource optimization, achieving $800,000 in annual savings in transportation scheduling through enhanced real-time rescheduling capabilities. 🔹Expanded the team from 3 to 8 members, overcoming challenges through pair programming and comprehensive onboarding, while implementing 9 serverless products that garnered 5 million views. 🔹Automated processes by creating 42 solutions that replaced manual tasks such as data entry and report generation, utilizing RPA and custom scripts, resulting in over 30,000 man-hours saved annually. ### Support Engineer @ Amazon Jan 2014 – Jan 2016 | Hyderabad, Telangana, India 🔹Developed a web-based R-Shiny scheduling tool, replacing an Excel-based system and addressing inefficiencies such as manual data entry errors and lack of real-time updates, resulting in a 60% improvement in scheduling efficiency and an 80% reduction in scheduling-related errors. 🔹Maintained a 94% average productivity in the Inbound Frontline team through the implementation of a tiered support system, a comprehensive knowledge base, and regular training sessions, achieving performance 15% above the Amazon average and 10% higher than the previous year. 🔹Transitioned to the IPEX team, delivering high-impact projects for Supply Chain Operations, including an automated inventory reconciliation system that reduced discrepancies by 40%, a predictive maintenance system that cut equipment downtime by 30%, and a dynamic load balancing system that improved dock utilization by 25%. ## Education ### Bachelor of Science - BS in Economics Osmania University, Hyderabad ## Contact & Social - LinkedIn: https://linkedin.com/in/misbahuddinmohammed - Portfolio: https://misbahuddin.net --- Source: https://flows.cv/misbahuddin JSON Resume: https://flows.cv/misbahuddin/resume.json Last updated: 2026-04-18