Go Backend Engineer - Microservices, Cloud & CI/CD

Machine Learning Technologies, LLC; Atlanta (GA); On-site; USD 120,000 - 170,000; Full time

Job summary

Machine Learning Technologies, LLC in Atlanta, GA, is seeking a skilled Go backend engineer to design, build, and maintain scalable services. You will develop RESTful and GraphQL APIs, implement microservices, and optimize performance in distributed systems.

Candidates will work with PostgreSQL, MySQL, MongoDB, Redis, and message brokers like Kafka and RabbitMQ; containerized deployments with Docker and Kubernetes; cloud offerings on AWS/AZ/ GCP; and CI/CD pipelines with Jenkins or GitHub

Qualifications

• Design, develop, and maintain scalable backend applications using Go.
• Develop RESTful APIs, GraphQL APIs, and backend services.
• Design and develop microservices-based architectures using Golang.
• Implement authentication and authorization using OAuth 2.0, JWT, and API security standards.
• Develop asynchronous processing and messaging solutions using Kafka and RabbitMQ.

Responsibilities

• Design, develop, and maintain scalable backend applications using Go.
• Develop RESTful APIs, GraphQL APIs, and backend services.
• Build microservices-based architectures and distributed systems.
• Implement authentication and authorization using OAuth 2.0 and JWT.
• Collaborate with architects, DevOps, QA teams, and stakeholders.
• Participate in Agile ceremonies and code reviews.

Skills

Go / Golang

RESTful APIs

GraphQL

Microservices

SQL & NoSQL

Authentication / OAuth 2.0 JWT

Tools

Docker

Kubernetes

PostgreSQL

MySQL

MongoDB

Redis

Kafka

RabbitMQ

GitHub Actions

Job description

Machine Learning Technologies, LLC in Atlanta, GA, is seeking a skilled Go backend engineer to design, build, and maintain scalable services. You will develop RESTful and GraphQL APIs, implement microservices, and optimize performance in distributed systems.

Candidates will work with PostgreSQL, MySQL, MongoDB, Redis, and message brokers like Kafka and RabbitMQ; containerized deployments with Docker and Kubernetes; cloud offerings on AWS/AZ/ GCP; and CI/CD pipelines with Jenkins or GitHub