Solutions Architect | Senior Software Engineer | Healthcare Technology

Results-driven Solutions Architect with 6+ years of expertise in designing and delivering enterprise-grade cloud, AI, and ML solutions that drive digital transformation. Specialized in architecting scalable, secure, and AI-driven ecosystems that enhance operational efficiency and innovation. Proven track record of migrating legacy systems to cloud-native architectures, optimizing costs, and integrating cutting-edge AI models for automation and analytics. Adept at balancing technical feasibility with business impact, excelling in multi-cloud, hybrid, and AI-enabled solutions while ensuring seamless integration and high-performance architectures.

• Go (Golang) - Primary language for high-performance backend services and microservices
• Java - Enterprise application development and legacy system modernization
• Python - AI/ML model development, data engineering, and automation frameworks
• C - System programming and performance-critical applications

• AI Model Integration: Transformers, Vision Transformers for automation and NLP
• ML Frameworks: Hugging Face, TensorFlow, PyTorch for model development and deployment
• LLM Deployment: vLLM, Ollama for efficient large language model serving and inference
• Model Optimization: Pruning, quantization for reduced inference time and resource usage
• Predictive Analytics: Fine-tuned models for fraud detection and business intelligence
• Computer Vision: Image analysis and processing using advanced ML techniques
• Model Serving: High-performance inference engines and scalable model deployment pipelines

• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP) with expertise in multi-cloud strategies
• Serverless Computing: Lambda functions, serverless architecture patterns
• Infrastructure as Code: Terraform, CloudFormation for automated provisioning
• Cost Optimization: Auto-scaling, spot instances, and resource optimization strategies
• Cloud Security: IAM, encryption, GDPR and HIPAA compliance implementation

• Containerization: Docker, Kubernetes cluster management and orchestration
• Container Packaging: Helm charts for deployment, distribution, and versioning
• CI/CD Pipelines: Automated deployment and continuous integration practices
• Monitoring: Datadog, Grafana for comprehensive system observability
• Infrastructure Automation: Consistent, repeatable deployment strategies

• Relational Databases: PostgreSQL, MySQL, Microsoft SQL Server for transactional systems
• NoSQL Databases: MongoDB for document-based data modeling and flexible schemas
• In-Memory Caching: Redis for high-performance caching and session management
• Search & Analytics: Elasticsearch for full-text search, logging, and real-time analytics
• Database Optimization: Query tuning, indexing strategies, and performance monitoring
• Data Replication: Master-slave configurations, clustering, and high-availability setups

• ETL Pipelines: Data extraction, transformation, and loading at enterprise scale
• Workflow Management: Apache Airflow for complex data workflows and pipeline orchestration
• Data Governance: Metadata management, data lineage, and transparency practices
• Big Data: Apache Spark, distributed data processing systems
• Data Optimization: Performance tuning and data model optimization for insights
• Real-time Processing: Stream processing and real-time analytics systems

• System Integration: Legacy system migration to microservices architecture
• API Development: RESTful APIs, GraphQL, enterprise-grade service design
• Security Implementation: End-to-end encryption, secure coding practices
• Compliance: GDPR, HIPAA, and industry-standard compliance frameworks
• Performance Optimization: Sub-second response times and scalability improvements

Sep 2024 - Present

• Architect scalable, cloud-native solutions leveraging serverless, Docker, and Kubernetes for digital transformation
• Develop and optimize ETL pipelines and data models, transforming raw data into actionable business insights
• Lead migration of legacy systems to microservices architecture, enhancing scalability and accelerating feature delivery
• Implement cloud cost optimization strategies using auto-scaling, serverless architecture, and spot instances
• Integrate AI models (transformers, Vision Transformers) for automation, NLP, and image analysis capabilities
• Fine-tune pre-trained models for fraud detection and predictive analytics, deploying at scale on AWS and Azure
• Apply AI model optimization techniques (pruning, quantization) to reduce inference time and resource usage
• Automate infrastructure with IaC (Terraform, CloudFormation) for consistent, repeatable deployments
• Strengthen cloud security with IAM, encryption, and compliance measures aligning with GDPR and HIPAA
• Establish metadata management practices ensuring data lineage, governance, and transparency
• Collaborate with stakeholders to align technical solutions with business needs, increasing product adoption

Jun 2019 - Sep 2024

• Built highly scalable, performant, and fault-tolerant applications for major pharmaceutical companies serving 9+ Asian markets
• Increased application performance by optimizing code and API architecture, reducing response times to sub-seconds
• Identified and resolved routine program challenges, proposing well-researched solutions for complex technical problems
• Worked extensively in Agile development environments to assess progress toward program goals and objectives
• Engaged with potential customers as lead developer, providing technical guidance to drive customer success and product adoption
• Strategically optimized cloud infrastructure, achieving remarkable cost reduction while fortifying network security
• Improved product availability and fault tolerance through dynamic horizontal scaling, ensuring uninterrupted service
• Architected and developed cloud-native product versions on Kubernetes, packaged as Helm charts for easy deployment
• Established robust Kubernetes cluster monitoring through Datadog & Grafana for comprehensive observability
• Applied Agile methodologies with continuous improvement mindset for iterative development and timely delivery
• Led R&D initiatives exploring emerging technologies and innovative solutions to drive business growth
• Maintained comprehensive technical documentation ensuring knowledge sharing and facilitating future development

• Architected cloud-native solutions using serverless computing and container orchestration
• Integrated transformers and Vision Transformers for automated NLP and image analysis
• Implemented real-time data processing pipelines for actionable business insights
• Achieved significant cost optimization through intelligent resource allocation

• Built highly scalable application serving 9+ Asian markets for major pharmaceutical company
• Optimized performance achieving sub-second response times through code and architecture improvements
• Implemented dynamic horizontal scaling ensuring 99.9% uptime and fault tolerance
• Deployed cloud-native Kubernetes solutions packaged as Helm charts

• Led complete migration from monolithic to microservices architecture
• Automated infrastructure provisioning using Terraform and CloudFormation
• Established comprehensive monitoring with Datadog and Grafana
• Reduced operational costs while improving system reliability and scalability

• Fine-tuned pre-trained models for fraud detection and predictive analytics
• Deployed large language models (LLMs) using vLLM and Ollama for efficient inference
• Applied model optimization techniques (pruning, quantization) for efficient inference
• Deployed ML models at scale on AWS and Azure with automated CI/CD pipelines
• Implemented robust security and compliance measures for sensitive data processing
• Built high-performance model serving infrastructure for real-time applications

Bachelor of Technology in Computer Science & Engineering
Asansol Engineering College | 2019

• Problem Solving Through Programming in C - NPTEL
• Docker Essentials: A Developer Introduction - IBM
• Learning Java 8 - LinkedIn Learning
• Go Design Patterns - LinkedIn Learning
• AWS Essential Training for Developers - AWS
• Apache Kafka Essential Training: Getting Started - LinkedIn Learning
• Getting Started with the AWS Cloud Essentials - AWS
• Apache Spark Essential Training: Big Data Engineering - LinkedIn Learning

• Team of the Quarter (Jan 2021) - Technology Solutions Provider
• Employee of the Month (Jun 2020) - Technology Solutions Provider
• Outstanding Teamwork Award - Technology Solutions Provider

• Email: [email protected]
• LinkedIn: linkedin.com/in/supratick-dey-81285315b
• Portfolio: supratickdey.live
• Location: Available for remote opportunities

Open to new opportunities in backend development, cloud architecture, and healthcare technology solutions.