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Weekday, Inc.

Full Stack Engineer

Reposted 5 Days Ago
In-Office
San Francisco, CA, USA
180K-250K Annually
Senior level
In-Office
San Francisco, CA, USA
180K-250K Annually
Senior level
Build and deploy AI-driven web applications across frontend and backend. Design scalable backend systems, responsive TypeScript frontends, ETL pipelines, and integrate ML models into production. Work with cloud platforms, containerization, APIs, automated testing, and cross-functional teams to deliver robust, high-performance solutions.
The summary above was generated by 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.


RequirementsKey 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.
Required Skills & Qualifications
  • 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.
Preferred Qualifications
  • 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.

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