Python Platform Engineer (AI & Distributed Systems)

Mitchell Martin
Jersey City, NJ, United States
15 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$145,600.0 - $187,200.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Application Integration Architecture Cloud Engineering Computer Programming Distributed Systems Python (Programming Language) Message Oriented Middleware Systems Integration Web Application Frameworks Event Driven Architecture Restful APIs Automation Anywhere
+2 more
Legacy Systems Microservices

Job description

This role involves designing, building, and maintaining Python platforms for scalable, enterprise systems in Jersey City, NJ. It is a contract position focused on backend engineering with an emphasis on distributed systems and AI integration. The engineer will collaborate with senior engineers and architects to modernize systems and integrate emerging AI technologies. Design and maintain production-grade Python platforms for enterprise systems. Focus on backend engineering with distributed systems and AI integration. Work within a regulated environment to modernize legacy systems. Integrate AI technologies and deliver resilient services. Ensure compliance with security, governance, and risk management standards. Build reusable platform components and align with architectural direction., Architect and implement Python-based applications and services. Design distributed systems with concurrency and resiliency. Build and productionize AI workflows and model integration. Implement event-driven patterns using asynchronous messaging. Collaborate with architects to align solutions with enterprise standards.

Requirements

Strong Python engineering background in platforms and distributed systems. Experience with microservices, REST APIs, and event-driven architectures. Hands-on experience with Python frameworks. Familiarity with async programming and service orchestration. Understanding of cloud-native architecture and operational best practices.

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