14mo ago

Full Stack Engineer

United States·San FranciscoFull-timemid

EngineeringFullstack Developer

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Quick Summary

Key Responsibilities

Design, develop, and deploy high-quality AI-driven web applications, ensuring performance, scalability, and maintainability across both frontend and backend.

Requirements Summary

Design, develop, and deploy high-quality AI-driven web applications, ensuring performance, scalability, and maintainability across both frontend and backend.

Technical Tools

EngineeringFullstack Developer

Requirements

~1 min read

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.

Responsibilities

~1 min read

→ 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.