Arturs Kristaps Grabovskis
I am a versatile Full Stack Python Developer with 11 years of experience building scalable web applications and AI-driven solutions. js, FastAPI, SQL database management, and cloud platforms including AWS and Azure.
About
I am a versatile Full Stack Python Developer with 11 years of experience building scalable web applications and AI-driven solutions. I am proficient in Java, Python, React.js, FastAPI, SQL database management, and cloud platforms including AWS and Azure. I specialize in implementing LLM fine-tuning, vector search with Hugging Face, and semantic ETL pipelines.
I am passionate about leveraging cutting-edge technology to deliver efficient, data-driven applications that solve complex business problems. I enjoy continuous learning, collaborating with teams, and applying innovative solutions in agile environments with a cloud-first mindset.
- 11 years' experience
- Joined August 2025
Industry experience
- Financial Services
- Healthcare
- Software & Internet
Work experience· 12 roles
Developed backend systems using Python and optimized SQL database interactions for large-scale financial data processing, reducing manual workflows by 60% and achieving sub-50ms latency. Integrated OpenAI API for customer support automation, reducing ticket resolution time by 45%. Engineered AI-driven fraud detection systems with TensorFlow and PyTorch, improving fraud response times by 20%. Built full-stack features using React.js and FastAPI; migrated a monolithic CMS to Next.js microservices on Kubernetes, improving release cycles. Collaborated with stakeholders to optimize business process flows.
Developed robust backend systems using Java and optimized SQL databases for large-scale financial data, reducing manual workflows by 60% and achieving sub-50ms latency via ETL pipelines and microservices. Engineered AI-driven fraud detection with Python and TensorFlow/PyTorch, enabling real-time analytics and improving fraud response time by 20%. Built full-stack features with React.js and Java Spring Boot, integrating RESTful APIs and deploying containerized applications on Azure cloud, enhancing user experience and reliability. Reduced cloud infrastructure costs by 40% through DevOps automation and memory profiling. Collaborated with stakeholders to optimize process flows in compliance with customer and regulatory needs.
Developed robust backend systems with Java and optimized SQL databases for large-scale financial data processing, reducing manual workflows by 60% and achieving sub-50ms latency. Engineered AI-driven fraud detection systems using Python with TensorFlow, PyTorch, and NLP techniques for real-time data analysis, resulting in 20% faster fraud incident response times. Built and maintained full-stack web applications with React.js and Java, integrating RESTful APIs and deploying containerized applications on cloud platforms such as Azure. Reduced cloud infrastructure costs by 40% through DevOps automation and memory profiling. Collaborated with business stakeholders to align solutions with customer needs and regulatory requirements.
Education
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