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Hi, I'm Rameez Muhammad Khan, a full-stack engineer with 4+ years building AI products and high-scale data systems. I've shipped an LLM-powered clinical tool that cuts chart review from 5+ minutes to under 30 seconds for 100k+ users, and built an end-to-end real estate intelligence platform handling 1B+ geospatial rows. I thrive across the full product lifecycle—from architecture and API design to production AWS deployments and data pipelines. I enjoy collaborating with cross-functional teams to turn ambitious ideas into reliable software.…Hi, I'm Rameez Muhammad Khan, a full-stack engineer with 4+ years building AI products and high-scale data systems. I've shipped an LLM-powered clinical tool that cuts chart review from 5+ minutes to under 30 seconds for 100k+ users, and built an end-to-end real estate intelligence platform handling 1B+ geospatial rows. I thrive across the full product lifecycle—from architecture and API design to production AWS deployments and data pipelines. I enjoy collaborating with cross-functional teams to turn ambitious ideas into reliable software.

Rameez Muhammad Khan

Full Stack Developer, Web Developer, Back-End Developer, +2

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Hi, I'm Rameez Muhammad Khan, a full-stack engineer with 4+ years building AI products and high-scale data systems. I've shipped an LLM-powered clinical tool that cuts chart review from 5+ minutes to under 30 seconds for 100k+ users, and built an end-to-end real estate intelligence platform handling 1B+ geospatial rows. I thrive across the full product lifecycle—from architecture and API design to production AWS deployments and data pipelines. I enjoy collaborating with cross-functional teams to turn ambitious ideas into reliable software.…Hi, I'm Rameez Muhammad Khan, a full-stack engineer with 4+ years building AI products and high-scale data systems. I've shipped an LLM-powered clinical tool that cuts chart review from 5+ minutes to under 30 seconds for 100k+ users, and built an end-to-end real estate intelligence platform handling 1B+ geospatial rows. I thrive across the full product lifecycle—from architecture and API design to production AWS deployments and data pipelines. I enjoy collaborating with cross-functional teams to turn ambitious ideas into reliable software.

Available to hire

Hi, I’m Rameez Muhammad Khan, a full-stack engineer with 4+ years building AI products and high-scale data systems. I’ve shipped an LLM-powered clinical tool that cuts chart review from 5+ minutes to under 30 seconds for 100k+ users, and built an end-to-end real estate intelligence platform handling 1B+ geospatial rows.

I thrive across the full product lifecycle—from architecture and API design to production AWS deployments and data pipelines. I enjoy collaborating with cross-functional teams to turn ambitious ideas into reliable software.

Skills

Experience Level

Expert

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Expert

Work Experience

Hybrid Software Engineer at Contour Software

June 1, 2022 - Present

Shipped an LLM-powered clinical documentation system (Azure AI Foundry) that generates patient summaries, structured reports, and care recommendations from medical history, reducing chart review time from 5+ minutes to under 30 seconds per patient. Built end-to-end features across a 100k+ user patient care platform (scheduling with bulk cancellation and multi-view calendars, real-time messaging with file uploads and search, and caregiver workflows). Led a TypeScript migration of the Next.js codebase with typed API contracts across components to eliminate runtime type errors and enable safe large-scale refactoring. Standardized server-state management with Redux Toolkit (RTK Query) across 25+ API endpoints, reducing duplicated fetch logic and race conditions and improving navigation speed.

Remote Software Engineer (Contract) at StreetSpring

May 1, 2025 - Present

Designed and delivered a commercial real estate intelligence platform covering 24 US metro areas — Mapbox-based property search, geospatial location scoring, and a full SaaS subscription product. Built an 18-step Python data pipeline ingesting census, spending, walkscore, and competitor data to generate survivability scores using a BigML ensemble model. Optimized ML inference by moving from row-based processing to vectorized NumPy/CuPy batch execution across 1B+ rows, reducing per-city runtime from 4+ hours to ~15 minutes. Implemented a Stripe billing system supporting subscriptions, passes, and invoices with idempotent webhook handling; integrated Mixpanel for funnel and revenue tracking. Deployed on AWS within a private VPC using CloudFront, SSM, and layered security groups; implemented an outbox pattern with SQS and dead-letter queues for reliable event processing. Designed a Backend-for-Frontend (BFF) architecture with rate limiting and shared-secret validation to keep all backen

Remote Contract at ScoopAI

January 1, 2023 - Present

Built an end-to-end AI news-to-podcast pipeline for a client using OpenAI GPT-4 and Listnr TTS — automated article ingestion, SSML script generation, top-10 story curation by category, and S3-backed episode delivery. Developed a Scrapy ingestion engine with 10 site-specific spiders, YAML-driven config, concurrent execution, and pandas-based deduplication across politics, business, and technology feeds.