
With over 5 years of experience as a Lead Software Engineer and Backend Specialist, I focus on building scalable cloud systems, AI-driven pipelines, and robust web data platforms. My expertise includes Python, GCP, AWS, Kubernetes, Terraform, Ansible, various data technologies like BigQuery and ClickHouse, and backend frameworks like Django, Flask, and FastAPI. Holding a Bachelor of Technology in Computer Science and Engineering, I leverage my skills to design and implement efficient, high-performance solutions that drive business success, particularly through infrastructure automation and data processing at scale.
Let's TalkDesigning and managing Cloud Infrastructure in AWS and GCP
Automating infrastructure with Terraform and Ansible scripts
Dockerizing applications and managing containers using AWS ECR and Kubernetes
Setting up CI/CD pipelines for automated build and deployment processes
Integrating cloud services for optimized performance and scalability
Building robust backend systems with Django and Flask
Creating and managing RESTful APIs for seamless frontend-backend integration
Implementing authentication and authorization using OAuth and JWT
Configuring database solutions for both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
Processing ETL jobs and automated tasks with Celery and Apache Airflow
Designing and training machine learning models for predictive analytics and decision making
Developing specialized models for image processing and natural language processing
Applying transfer learning to leverage state-of-the-art pre-trained models
Optimizing ML models for performance in real-time applications
Fine-tuning state-of-the-art large language models such as GPT for tailored business applications, enhancing decision-making and automation.

Led transition to scalable GCP infra, improving efficiency >50%. Automated deployments with Terraform/Ansible for Kubernetes/Dataproc.
Technologies: GCP, Kubernetes, Terraform, Ansible, MongoDB, Dataproc
Engineered pipelines processing millions of pages/month. Utilized Parquet, GCS, BigQuery, ClickHouse for batch/streaming analytics & SEO reporting.
Technologies: GCS, BigQuery, ClickHouse, Parquet, PyArrow, Python, Kubernetes, Grafana
Developed AI prompting system using LLMs to generate SEO keywords from crawl data, integrating page sampling and prompt tuning.
Technologies: Python, LLM APIs, Prompt Engineering
Led migration of a monolithic app to microservices using job queues (Redis/Kafka) for inter-service communication.
Technologies: Python, Redis, Kafka, MongoDB, Elastic Search, GCP
Developed a deep learning solution for e-commerce product matching using multimodal architectures and various text embeddings.
Technologies: TensorFlow, Python, GCP, BERT, SpaCy, Flair, FastText