I am an AI Engineer with strong Python and Go backend experience, focused on building tools that empower developers through open-source contributions. My passion lies in crafting foundational pipelines and systems from scratch, enabling efficient and reliable AI solutions.

• Building foundational infrastructure to support the deployment and scalability of Large Language Models (LLMs).
• Creating and refining end-to-end pipelines for integrating LLMs into production environments.
• Developing systems for real-time inference, model versioning, and monitoring.
• Optimizing resource utilization for LLM-based services in cloud and hybrid environments.
• Designing document management systems tailored for LLM workflows, including storage, retrieval, and efficient indexing.

• Strong foundation in Python and DevOps tools for AI applications.
• Expertise in designing pipelines and systems from the ground up.
• Practical approach to operationalizing AI with a focus on performance and cost efficiency.

• Expertise in designing secure systems using hashing, JWT, HMAC, and RSA.
• Implemented app integrity measures to ensure secure operations and prevent unauthorized access.
• Familiar with integrating social authentication services.

• Extensive experience with containerization (Docker) and orchestration for deploying AI solutions.
• Proficient in AWS and GCP for scalable cloud-based LLM infrastructure.
• Skilled in automation and infrastructure-as-code using Terraform for deployment consistency.

• LLM Deployment Pipeline: Designed an end-to-end pipeline for deploying LLMs with auto-scaling, logging, and monitoring.
• Inference Optimization: Developed systems for real-time LLM inference with reduced latency and optimized hardware utilization.
• Model Serving Infrastructure: Built a secure and scalable model serving framework using AWS Fargate and API Gateway.
• Document Management System for LLMs: Built a tailored document system for efficient data storage, retrieval, and indexing to support LLM operations.
• Contact Tracing System: Developed a backend system for pandemic response, emphasizing secure authentication and deployment.
• Sensor Data Analysis: Designed an Android-based application to collect and analyze sensor data for research purposes, integrating it with GCP for storage and processing.

• Explore Rust to contribute to better Python tools and enhance AI-related development workflows.
• Actively engage in open-source projects, focusing on tools and libraries for AI and infrastructure.
• Develop expertise in building simple and effective web and mobile applications to complement backend and AI systems.
• Advance knowledge in creating robust pipelines for LLM integration and optimization.
• Drive innovations in scalable, cost-effective AI deployment architectures.