Full stack Engineer

Overview We’re looking for a Full Stack Developer skilled in building scalable web applications using React / Next.js on the frontend and Python frameworks (Django and FastAPI) on the backend. You’ll work closely with product, design, and DevOps teams to deliver reliable, high-performing applications hosted on AWS, backed by PostgreSQL and Snowflake. We value developers who leverage modern AI-assisted development tools such as Cursor and Claude Code to accelerate delivery and maintain code quality. Key Responsibilities • Design, develop, and maintain full-stack web applications using React / Next.js on the frontend and Django or FastAPI on the backend. • Build secure, scalable RESTful and async APIs; integrate with third-party services as needed. • Manage PostgreSQL databases with efficient schema design, migrations, and optimized queries. • Work with Snowflake for data warehousing needs – build and maintain data models, write performant queries, and integrate warehouse data into application layers. • Translate UI/UX wireframes into responsive, accessible, high-quality frontend components. • Implement authentication, authorization, and session management (JWT, OAuth2). • Set up and manage AWS infrastructure for deployments, CI/CD pipelines, and horizontal scalability. • Leverage AI-assisted development tools (Cursor, Claude Code) to accelerate coding workflows, generate boilerplate, write tests, and improve code reviews. • Write clean, maintainable, and well-documented code with comprehensive test coverage. • Troubleshoot, debug, and optimize performance across the entire stack. Technical Skills Frontend • React.js, Next.js, TypeScript, Tailwind CSS • State management (Redux, Context API, Zustand) • Responsive and accessible UI design principles • Component-driven architecture and design systems Backend • Python (Django / Django REST Framework / FastAPI) • REST and async API design; WebSocket support • Authentication and authorization (JWT, OAuth2, session-based) • ORM and data modeling (Django ORM, SQLAlchemy, Tortoise ORM) • Task queues and background processing (Celery, Redis) Database & Data Warehousing • PostgreSQL – schema design, migrations, indexing, and performance tuning • Snowflake – data warehousing, writing optimized SQL queries, managing schemas, stages, and pipes for data ingestion • Experience connecting application backends to Snowflake using Python connectors (snowflake-connector-python, SQLAlchemy with Snowflake dialect) • Experience with Redis or other caching layers Cloud & DevOps • AWS (EC2, S3, RDS, Lambda, CloudFront, API Gateway) • Docker and container-based deployment • CI/CD with GitHub Actions / AWS CodePipeline • Basic server and infrastructure management AI-Assisted Development • Hands-on experience with Cursor IDE for AI-powered code editing, multi-file refactoring, and inline code generation • Proficiency in Claude Code (CLI) for agentic coding tasks – scaffolding projects, writing tests, debugging, and automating repetitive workflows • Ability to write effective prompts and system instructions to get high-quality outputs from AI coding assistants • Familiarity with integrating AI tools into CI/CD pipelines (e.g., automated code review, PR summarization) Qualifications • Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). • 2+ years of hands-on full-stack development experience with React and Python-based backend frameworks. • Demonstrated experience using AI-assisted development tools (Cursor, Claude Code, or similar) in production workflows. • Strong understanding of API-driven architectures, microservices patterns, and cloud-native environments. • Excellent problem-solving, debugging, and cross-team collaboration skills. • Familiarity with version control best practices (Git, branching strategies, code reviews). Nice to Have • Experience with GraphQL or gRPC. • Knowledge of serverless architectures (AWS Lambda, Step Functions). • Contributions to open-source projects. • Experience building or consuming AI/ML APIs and LLM-powered features. • Familiarity with infrastructure-as-code tools (Terraform, CDK). • Experience with Snowflake performance tuning, materialized views, and data pipeline orchestration (dbt, Airflow).