I'm a Technical Lead specializing in end-to-end product development — from architecting scalable backends to building intuitive frontends and deploying AI/ML solutions in production. With 6+ years of experience, I've led engineering teams to ship enterprise-grade platforms that handle millions of requests while maintaining 99%+ uptime.
What drives me: Turning complex business problems into elegant, scalable technical solutions that create measurable impact.
class EhtishamSadiq: def __init__(self): self.role = "Technical Lead & Senior Full-Stack Engineer" self.location = "Pakistan 🇵🇰" self.experience = "6+ years" self.team_leadership = "3-8 engineers" def current_focus(self): return { "architecture": "Microservices & Event-Driven Systems", "ai_ml": "LangChain, RAG, Production ML Pipelines", "cloud": "AWS, GCP, Docker, Kubernetes", "leadership": "Technical Strategy & Team Mentorship" } def fun_fact(self): return "I optimize code for performance AND readability" me = EhtishamSadiq() print(me.fun_fact())Full-Stack Engineering
- Architecting scalable SaaS platforms from MVP to enterprise scale
- Building responsive frontends with React.js, Next.js, TypeScript
- Designing RESTful APIs & microservices with FastAPI, Django, Node.js
- Optimizing database performance with PostgreSQL, MySQL, MongoDB, Redis
AI/ML Engineering
- Implementing production ML pipelines with MLOps best practices
- Building conversational AI systems with LangChain, LangGraph, OpenAI
- Deploying models on AWS SageMaker and cloud infrastructure
- Creating data pipelines with Apache Spark, Prefect, Celery
System Architecture & Leadership
- Leading cross-functional teams of 3-8 engineers
- Designing event-driven architectures with RabbitMQ, Kafka
- Implementing CI/CD pipelines with Docker, Kubernetes, GitHub Actions
- Achieving 40-85% performance improvements across systems
Tech Lead @ ThinkRealty Real Estate (March 2025 - Present)
Building the Future of Real Estate SaaS
Leading end-to-end development of a unified platform that eliminates data silos and automates lead management.
const impact = { teamSize: 5, apiPerformance: "< 200ms response time", dataAutomation: "70% reduction in manual entry", leadNurture: "< 5 min response time" }Key Achievements:
- Multi-Agent Lead Nurture System: Built intelligent system using LangGraph that scores leads with GPT-4, auto-routes to agents, and runs 5-12 touch nurture campaigns via SMS/WhatsApp/Email
- High-Performance Architecture: FastAPI backend + Next.js frontend + PostgreSQL achieving <200ms response times for complex queries
- Automated Data Pipelines: Integrated Apify web scraping with multiple APIs (Property Monitor, Bayut, PropertyFinder) for 70% auto-population
- DevOps Excellence: Implemented CI/CD pipelines with Docker containerization
Full-Stack AI Engineer @ VirtualFusion.ai (Jan 2025 - May 2025)
Enterprise Security Analysis Platform
Architected multi-tenant security platform processing 10K+ security advisories with 99.5% uptime.
Technical Highlights:
- Event-Driven Microservices: Built scalable architecture using RabbitMQ, Docker, achieving sub-500ms API responses
- Intelligent IoT Collection: Developed FastAPI microservice with Playwright MCP and AWS Textract, processing 1000+ devices at 95%+ accuracy
- Multi-Agent Chatbot: Implemented using LangGraph with Tavily search, achieving 90%+ relevance through semantic search optimization
- Automation Impact: Reduced manual security analysis time by 85%, enabling sub-2-minute network infrastructure analysis
Tech Stack: Django/DRF, PostgreSQL, TimescaleDB, RabbitMQ, Docker, Auth0, AWS Textract, LangGraph
const frontend = { frameworks: ['React.js', 'Next.js'], languages: ['TypeScript', 'JavaScript'], styling: ['Tailwind CSS', 'CSS3', 'HTML5'], state: ['Redux', 'Context API'] }backend = { 'languages': ['Python', 'Node.js', 'Java'], 'frameworks': ['FastAPI', 'Django', 'Flask'], 'apis': ['RESTful', 'GraphQL', 'gRPC'], 'architecture': ['Microservices', 'Event-Driven'] }-- Expertise in: PostgreSQL ⚡ MySQL ⚡ MongoDB TimescaleDB ⚡ Redis ⚡ Vector DBs ArangoDB ⚡ SQL Optimization | ai_ml_stack = { 'frameworks': ['PyTorch', 'TensorFlow', 'Keras'], 'llm_tools': ['LangChain', 'LangGraph', 'OpenAI'], 'nlp': ['SpaCy', 'BERT', 'Transformers'], 'data': ['Pandas', 'NumPy', 'Apache Spark'], 'mlops': ['MLflow', 'AWS SageMaker'] }Cloud Platforms: - AWS: EC2, S3, Lambda, RDS, SageMaker, Textract - GCP: Compute Engine, Cloud Functions - Azure: App Services DevOps: - Containers: Docker, Kubernetes - CI/CD: GitHub Actions, Jenkins - Orchestration: Prefect, Celery - Monitoring: CloudWatch, Prometheusrealtime = { queues: ['RabbitMQ', 'Kafka', 'Redis Queue'], protocols: ['WebSockets', 'gRPC'], workers: ['Celery', 'Bull'] } |
| Tech: FastAPI, OpenAI, STT/TTS, AWS Production-grade interview system serving thousands of users with enterprise reliability. Impact Metrics:
| Tech: Django, Celery, Redis, Apache Spark Led team of 3 to build FDCPA-compliant platform transforming client operations. Business Impact:
| Tech: LangChain, RAG, OpenAI, Vector DBs Intelligent advisory system helping founders make data-driven decisions. User Impact:
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| Company | Role | Duration | Key Achievement |
|---|---|---|---|
| RIVON.AI | Technical Lead – AI/Database Engineering | June 2024 - Jan 2025 | Led team of 8 engineers, delivered 3 major AI/ML projects on time |
| VACON.AI | Senior ML Engineer | Aug 2022 - June 2024 | Built platform generating 1200% revenue increase |
| Blink Co Tech | ML Engineer/Full-Stack Dev | Dec 2020 - June 2022 | Deployed conversational AI with 99.95% uptime |
| Certification | Provider | Focus Area |
|---|---|---|
| 🧠 Machine Learning Specialization | Coursera | ML Fundamentals & Algorithms |
| 🤖 Deep Learning Specialization | Coursera | Neural Networks & CNNs |
| 🐍 Python for Data Engineering | DataCamp | Data Pipelines & ETL |
I'm always excited to collaborate on challenging projects, discuss system architecture, or explore opportunities in Full-Stack Development, AI/ML Engineering, and Technical Leadership.
