Python Fullstack Developer (Enterprise AI Platform) @ Remote
Kaizen Technologies Inc
United States
1 day ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Cloud Computing
Databases
Extract Transform Load (ETL)
Database Queries
Django Web Framework
Graph Database
Python (Programming Language)
PostgreSQL
Neo4j
Search Technologies
+15 more
SQLAlchemy
TypeScript
ReactJS
Apache Spark
Backend
Fastapi
Information Technology
AWS Glue
React Redux
Api Design
Restful APIs
Data Pipelines
AWS EKS
Docker
Microservices
Job description
- Fullstack Engineering: Architect and write clean, scalable code using Python (FastAPI/Django) and React (TypeScript/Hooks), implementing state management via Redux or Context API.
- Backend & API Systems: Design high-performance RESTful APIs, utilizing async/await patterns and SQLAlchemy ORM within a distributed microservices architecture.
- AI & Graph Integration: Implement semantic search and OpenAI API integrations, working with specialized database paradigms like Neo4j (Cypher) alongside PostgreSQL.
- Data & Infrastructure: Collaborate with data teams on ETL/ELT pipelines (AWS Glue/Spark) and deploy containerized microservices using Docker and Kubernetes (AWS EKS).
Requirements
Role Overview: We are seeking a hands-on Senior Python Fullstack Developer with 10+ years of experience to design, build, and scale our AI-powered enterprise platform, CollateralIQ. In this role, you will lead end-to-end feature development across modern React frontends and asynchronous Python backends while driving the integration of cutting-edge AI features, specialized graph databases, and high-throughput data pipelines., * Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 10+ years of production experience in full-stack software development, database query optimization, and cloud-native systems.
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