Martin Cece THEA
Experienced Backend Engineer with over 6 years of expertise in designing and implementing scalable and reliable backend systems using Python and Django. Proficient in developing robust APIs, optimizing database interactions, and integrating third-party services. Skilled in leveraging Python frameworks and tools such as Flask, Celery, and Django Rest Framework, as well as AWS services (EC2, RDS, S3). Deep understanding of software architecture, design patterns, and DevOps practices. Seeking to apply my backend development skills in a challenging senior engineer role
REVIEWS FROM CLIENTS
Project Overview
Developed a cutting-edge Chatbot service leveraging Artificial Intelligence (AI) capabilitie...
Project Overview
Developed a cutting-edge Chatbot service leveraging Artificial Intelligence (AI) capabilities through integration with the OpenAI API and Langchain. The project aimed to create an intelligent conversational agent capable of understanding and responding to user queries in natural language
Key Contributions:
- Collaborated with stakeholders to gather requirements and define project objectives.
- Integrated the OpenAI API to harness advanced natural language processing models for response generation.
- Implemented Langchain for secure and decentralized data storage, ensuring privacy and integrity.
- Designed and developed the Chatbot's conversational logic and user interface.
- Conduct code reviews and collaborate with other developers to improve code quality.
- Deployed the Chatbot to a scalable infrastructure environment, ensuring high availability and performance.
- Documented architecture, design decisions, and implementation details for reference and future maintenance.
Technologies Used:
- AI Framework: OpenAI API, Langchain
- Programming languages: Python, Golang
- Version control: Git, GitHub, GitHub Actions
- Data storage: SQL databases, NoSQL databases
- Database management: PostgreSQL, MySQL, DynamoDB
- Cloud platforms: AWS, Google Cloud Platform
Project Description:
Led the development of a comprehensive monitoring and data management system for several...
Project Description:
Led the development of a comprehensive monitoring and data management system for several hundred solar panels across Europe. The project aimed to provide real-time insights into solar panel performance, maintenance needs, and energy production to optimize efficiency and ensure reliability.
Key Contributions:
- Collaborated with stakeholders to define requirements and objectives for the monitoring and data management system.
- Designed and implemented the architecture for collecting, storing, and analyzing data from solar panels.
- Developed data pipelines to ingest, process, and transform data from various sources, including sensors and IoT devices.
- Implemented real-time monitoring dashboards to visualize solar panel performance metrics and identify anomalies.
- Integrated predictive maintenance algorithms to anticipate and prevent potential issues with solar panel operations
- Conducted performance testing and optimization to ensure the scalability and reliability of the system
Technologies Used:
- Data collection: Sensors, IoT devices
- Data storage: SQL databases, NoSQL databases
- Data processing: Apache Spark, Apache Kafka
- Predictive analytics: Machine learning algorithms (e.g., regression, classification)
- Cloud platforms: AWS, Google Cloud Platform
- Version control: Git
- Deployment tools: Docker, Kubernetes
Project Description:
Pioneered the creation of a comprehensive platform for monitoring, inspecting, and monit...
Project Description:
Pioneered the creation of a comprehensive platform for monitoring, inspecting, and monitoring the performance of infrastructures and structures. The project aimed to provide real-time insights into the condition and behavior of critical assets to ensure safety, reliability, and efficiency
Key Contributions:
- Orchestrated collaborative brainstorming sessions with stakeholders to define requirements and objectives for the monitoring, inspection, and surveillance platform.
- Architected and engineered the framework for collecting, storing, and analyzing data from various sensors and monitoring devices, igniting innovation in data processing methodologies.
- Engineered sophisticated data processing pipelines to ingest, cleanse, and transform raw data into actionable insights, blazing a trail for advanced analytics in infrastructure monitoring.
- Crafted immersive real-time dashboards and visualization tools, painting vivid pictures of asset health and performance, and empowering stakeholders with insightful data narratives.
- Infused the platform with cutting-edge machine-learning algorithms for predictive maintenance and anomaly detection, fostering a culture of proactive asset management and disruption prevention.
Technologies used:
- Data collection: Sensors, IoT devices, CCTV cameras
- Data storage: SQL databases, NoSQL databases
- Data processing: Apache Spark, Apache Kafka
- Data visualization: Grafana, Kibana
- Machine learning: TensorFlow, scikit-learn
- Data governance: Data quality frameworks, encryption techniques
- Cloud platforms: AWS
- Version control: Git
- Deployment tools: Docker