Dimaag AI - Senior Backend Engineer - Python Programming

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DIMAAG

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Job Description

Role Summary

We are looking for a skilled Senior Backend Engineer with 3- 8 years of professional experience in developing scalable web applications and backend services. The ideal candidate will have strong expertise in FastAPI, along with experience in database design, CI/CD, and cloud environments.

Roles & Responsibilities

  • Design, develop, and maintain scalable backend services and APIs using FastAPI.
  • Develop and optimize web applications with a strong focus on performance, reliability, and security.
  • Design and manage relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB).
  • Collaborate with frontend, DevOps, product, and data science teams to deliver end-to-end solutions.
  • Integrate machine learning models and background task queues (e.g., Celery, Redis, RabbitMQ) into production systems.
  • Ensure high code quality through unit and integration testing (e.g., PyTest), peer reviews, and best practices.
  • Troubleshoot and resolve issues in development and production environments.
  • Implement CI/CD pipelines, manage deployments, and work closely with DevOps on automation.
  • Write and maintain technical documentation for APIs, services, and system workflows.

Required Skills & Qualifications

  • 3-8 years of professional experience in backend/full stack development with Python.
  • B.E / MTech sin Computer Science, IT, or related fields.
  • Hands-on experience with FastAPI (preferred), Flask, and/or Django in production environments.
  • Proficiency in designing and consuming RESTful APIs.
  • Strong database experience with SQL (PostgreSQL, MySQL) and familiarity with NoSQL (MongoDB).
  • Experience with Git/GitHub, Docker, and CI/CD pipelines.
  • Good understanding of asynchronous programming in Python.

Good To Have

  • Experience with Redis, Celery, or other background task queues.
  • Knowledge of GraphQL, WebSockets, microservices architecture.
  • Familiarity with Kubernetes or other container orchestration tools.
  • Exposure to cloud platforms such as AWS, GCP, or Azure.
  • Familiarity with real time stream processing and AI pipelines
  • Understanding of data science workflows, statistics, or mathematics concepts.

(ref:hirist.tech)

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