Frontend & Backend Engineer , AI Expert

Frontend Engineer

Skills
– HTML5, CSS3, JavaScript (ES6+), TypeScript
– Frameworks & Libraries: React.js, Angular, Vue.js, Next.js
– Responsive & Adaptive Design (Tailwind, Bootstrap, Material UI)
– State Management: Redux, Zustand, Vuex
– API integration (REST, GraphQL)
– Web performance optimization & accessibility (WCAG standards)
– Testing: Jest, Cypress, Playwright
– Version Control: Git, GitHub/GitLab

Experience
– Building user-friendly, scalable, and responsive web applications
– Cross-browser compatibility handling
– UI/UX collaboration with designers
– Deploying apps using Vercel, Netlify, or CI/CD pipelines

Backend Engineer

Skills
– Programming Languages: Node.js, Python, Java, Go, PHP, C#
– Frameworks: Express.js, Django, Flask, Spring Boot, .NET Core
– Databases: SQL (MySQL, PostgreSQL), NoSQL (MongoDB, Redis, Cassandra)
– API design & development (REST, GraphQL, gRPC)
– Authentication & Security (JWT, OAuth2, encryption, RBAC)
– Cloud Platforms: AWS, Azure, GCP
– Containerization & Orchestration: Docker, Kubernetes
– Testing: Mocha, Chai, JUnit, PyTest
– CI/CD: Jenkins, GitHub Actions, GitLab CI

Experience
– Designing and scaling microservices architecture
– Building high-performance APIs and backend systems
– Database schema design and optimization
– Handling concurrency, caching, and message queues (RabbitMQ, Kafka)
– Integrating third-party services (payment gateways, authentication, etc.)

AI Expert

Skills
– Machine Learning: Supervised/Unsupervised learning, Deep Learning
– Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras
– NLP: Transformers, BERT, GPT models, spaCy, NLTK
– Computer Vision: OpenCV, YOLO, CNNs
– Data Engineering: Pandas, NumPy, SQL, Spark
– Model Deployment: Flask, FastAPI, TensorFlow Serving, TorchServe, Docker
– MLOps: MLflow, Kubeflow, Airflow
– Cloud AI Services: AWS Sagemaker, GCP Vertex AI, Azure AI
– Prompt Engineering & LLM fine-tuning

Experience
– Developing and deploying AI/ML models for production
– Building recommendation systems, chatbots, and predictive analytics
– Training, fine-tuning, and optimizing deep learning models
– Handling large datasets and data pipelines
– Implementing real-time AI systems (speech recognition, image classification, etc.)