Tahir Murtaza

Led the architecture and design of scalable AI-based systems and new product features, driving clinical automation and operational efficiency.

Designed and deployed an AI Voice assistant for clinical research, automating patient screening and scheduling processes, reducing manual effort by 30%.

Developed real-time AI Agents with Vapi, FastAPI, Azure, Gemini, and OpenAI, streamlining complex scheduling workflows for intelligent automation.

Collaborated with cross-functional teams to deliver AI-driven solutions, reducing recruiter workload by 40% and boosting operational efficiency.

Managed end-to-end testing and production deployments, achieving 99.9% system reliability and optimal performance for AI services.

Identified and defined innovative use cases for AI models, leveraging prompt engineering to drive significant value and new solutions.

Conducted rigorous iterative testing of prompts, improving model output quality, reducing bias by 20%, and ensuring consistency.

Optimized prompts to reduce ambiguity by 15%, significantly maximizing the accuracy and relevance of LLM responses.

Analyzed AI-generated outputs and integrated user feedback, enhancing system efficiency by 10% and improving user satisfaction.

Engineered Python scripts for efficient bulk data loading into various stores, improving data processing efficiency by 25% through advanced business logic.

Pioneered a real-time product monitoring service using Python Scrapy and Selenium, improving competitive intelligence and inventory management.

Automated product migration across multiple stores with a bespoke Python FastAPI application, reducing migration time by 50%.

Architected and implemented a Python APScheduler-based scheduling service, enabling proactive order monitoring and reducing issue resolution time by 20%.

Developed a Python Sitemap Builder app, optimizing site crawling efficiency and indexing thousands of product URLs for enhanced SEO.

Automated data extraction from invoices and delivery notes using Angular Material and Java Spring Boot, increasing processing efficiency by 35%.

Ensured seamless software integration and efficient operation, providing users with accurate, timely insights that streamlined business operations by 20%.

Deployed and managed applications on AWS EC2, S3, and Lambda, enhancing scalability, storage, and leveraging serverless computing for cost efficiency.

Led a dynamic cross-functional team of 8+, proactively resolving issues and steering development efforts to ensure daily successful project delivery.

Architected a cutting-edge Resume and Job Scoring & Matching Engine using Django REST Framework, improving candidate evaluation precision by 25%.

Developed a modern Retail Management system with offline data syncing, utilizing Django REST Framework, Angular, and PostgreSQL, enhancing operational fluidity by 30%.

Conducted productive meetings with international clients, collaboratively defining product requirements and fostering strong relationships, resulting in 95% client satisfaction.