TOWSEEF ALTAF

• Developed and deployed a developer-focused AI support bot leveraging LLaMA (Large Language Model Meta AI) fine-tuned for contextual queries. Integrated CosmosDB for efficient data storage, reducing query resolution time by 60% and enabling real-time support for internal teams.
• Built a system to track developer productivity metrics, providing actionable insights through machine learning algorithms that predicted bottlenecks and improved team efficiency.
• Automated vulnerability detection and alerting using Python and AWS SNS, ensuring compliance with industry standards and reducing resolution time by 25%.
• Led an initiative to improve code quality across teams by implementing an AI-driven code coverage analysis pipeline, enhancing maintainability and reliability of core systems.

Key Skills Used:

• LLM Fine-Tuning, AI Model Deployment, Time Series Analysis, CI/CD Automation

• Designed and deployed a real-time recommendation system using GraphQL and Nest.js that analyzed user behavior patterns, improving API latency by 36% and enhancing user experience.
• Migrated messaging systems from RabbitMQ to Kafka, enabling high-throughput data streams with 28% fewer processing errors, crucial for marketplace-like ecosystems.
• Created predictive models to forecast system workload spikes, optimizing resource allocation and ensuring system stability during high-traffic periods.
• Built a monitoring infrastructure with DataDog and designed alerting mechanisms using anomaly detection algorithms, reducing mean time to resolution (MTTR) by 40%.
• Conducted A/B testing to assess the impact of feature rollouts, enabling data-driven decisions for UI/UX optimizations.

Key AI Skills Used:

• Recommendation Systems, Predictive Modeling, Event-Driven Architectures, Anomaly Detection

• Engineered an event-driven adapter service for processing 100,000 invoices per hour using AWS, achieving near-perfect accuracy and scalability for invoice standardization.
• Designed a schema migration solution to handle billions of rows in AWS RDS, leveraging machine learning-based data validation techniques to ensure data consistency with
• Reduced connection load on primary databases by 58% through a migration to read-only RDS replicas, using predictive algorithms to optimize query routing and resource usage.
• Built CI/CD pipelines with integrated automated tests using JUnit5, Mockito3, and AI-driven fault prediction, achieving 80% defect reduction post-release.

Key Skills Used:

• Event-Driven Architectures, Predictive Algorithms, Fault Detection

• Designed RESTful APIs for Bot360, a virtual interviewing platform, using Django and PostgreSQL, supporting real-time video analysis with facial recognition features.
• Developed ML models for candidate evaluation, incorporating natural language processing (NLP) for interview response analysis and automated scoring.
• Implemented geospatial features for recruiter-candidate matching, enhancing scheduling efficiency by 56%.

Key AI Skills Used

• NLP, Geospatial Data Processing, Facial Recognition