Full Stack Engineer
$180k - $250kWeekday AI
This role is for one of the Weekday's clients Salary range: $180k - $250k
Experience: 6+ YoE We are seeking an experienced Full Stack Engineer with a strong background in AI-driven application development , Python , TypeScript , and ETL pipelines . The ideal candidate will bring deep technical expertise across the stack, from designing and implementing scalable backend systems to creating intuitive and responsive frontends. You will play a key role in building, integrating, and optimizing systems that process and transform large datasets into actionable insights, leveraging AI technologies to deliver intelligent features. Requirements
Key Responsibilities
Experience: 6+ YoE We are seeking an experienced Full Stack Engineer with a strong background in AI-driven application development , Python , TypeScript , and ETL pipelines . The ideal candidate will bring deep technical expertise across the stack, from designing and implementing scalable backend systems to creating intuitive and responsive frontends. You will play a key role in building, integrating, and optimizing systems that process and transform large datasets into actionable insights, leveraging AI technologies to deliver intelligent features. Requirements
Key Responsibilities
- End-to-End Development: Design, develop, and deploy high-quality AI-driven web applications, ensuring performance, scalability, and maintainability across both frontend and backend.
- Backend Engineering: Build robust server-side applications using Python (FastAPI, Flask, or Django), integrating with databases, APIs, and AI/ML models.
- Frontend Development: Create engaging and responsive user interfaces with TypeScript (React.js, Next.js, or Angular), ensuring an exceptional user experience.
- AI Integration: Collaborate with data scientists to integrate machine learning models into production systems, ensuring seamless data flow and model performance monitoring.
- ETL Pipeline Development: Design, implement, and optimize ETL processes to efficiently collect, transform, and load large-scale datasets from multiple sources.
- API Design & Integration: Develop and consume RESTful and GraphQL APIs for communication between services and external systems.
- Cloud Deployment: Work with AWS, Azure, or GCP to deploy, scale, and monitor applications and ETL pipelines in production environments.
- Testing & Quality Assurance: Implement automated testing strategies (unit, integration, and end-to-end) to maintain software quality and reliability.
- Collaboration: Work closely with cross-functional teams including data engineering, AI research, product management, and UX design to deliver impactful features.
- Continuous Improvement: Stay current with emerging technologies, frameworks, and AI trends to propose innovative solutions and improve development practices.
- Experience: 6-10 years in full stack development, with at least 2-3 years in AI-driven application projects.
- Programming Expertise: Strong proficiency in Python for backend/API development and TypeScript for frontend applications.
- Frameworks: Hands-on experience with Python frameworks (FastAPI, Flask, Django) and TypeScript-based frontend frameworks (React, Angular, or Next.js).
- ETL & Data Engineering: Proven track record in designing and maintaining ETL pipelines and working with data processing tools (Airflow, dbt, or similar).
- Databases: Proficiency in relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, or similar).
- AI/ML Integration: Experience integrating AI/ML models into production workflows, preferably with TensorFlow, PyTorch, or scikit-learn.
- Cloud & DevOps: Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines, along with cloud services (AWS Lambda, S3, GCP BigQuery, Azure Data Factory).
- Problem Solving: Strong analytical and troubleshooting skills, with the ability to address technical challenges in complex systems.
- Collaboration: Excellent communication skills and a track record of working in agile, cross-functional teams.
- Prior experience with real-time data processing and streaming technologies (Kafka, Spark).
- Knowledge of MLOps best practices for model deployment and monitoring.
- Understanding of data governance, security, and compliance standards.
Vacancy posted 1 day ago
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