Role Overview:

We are seeking a Senior Python Backend Engineer with expertise in Python development, API engineering, workflow orchestration, automation, and DevOps practices. The ideal candidate will design, build, and maintain scalable backend applications, microservices, data workflows, and cloud-native solutions using modern Python technologies.

Key Responsibilities:

- Design, develop, and maintain backend applications and services using Python.

- Build and support RESTful APIs and microservices using FastAPI, Django, or Flask.

- Develop workflow orchestration and automation solutions using Apache Airflow.

- Design, optimize, and integrate databases including PostgreSQL, MySQL, and MongoDB.

- Implement and maintain CI/CD pipelines, deployment automation, and DevOps best practices.

- Build and support containerized applications using Docker and Kubernetes.

- Participate in code reviews, architecture discussions, production deployments, and continuous improvement initiatives.

- Document system architectures, APIs, workflows, and development standards.

Tech Stack:

- Python, FastAPI, Django, Flask, Apache Airflow, PostgreSQL, MySQL, MongoDB, Redis, Git, CI/CD, Docker, Kubernetes, Ansible, Linux/Unix.

Experience and Qualifications:

- 8+ years of experience in Python backend development and DevOps practices.

- Proven experience building scalable, production-grade backend systems.

- Strong experience with REST APIs, microservices, and distributed architectures.

- Hands-on experience with Docker, Kubernetes, and container orchestration.

- Experience implementing CI/CD pipelines and DevOps practices.

- Experience working in Agile, DevOps, or cloud-native environments.

- Good knowledge and hands-on experience in Virtualization (VMware), Storage, and Network.

- Working knowledge of Linux for deployment, troubleshooting, and operational support.

Nice to Have:

- Knowledge of Kafka, RabbitMQ, or other messaging and streaming platforms.

- Experience with Terraform, Ansible, Infrastructure as Code (IaC), and platform automation.

- Familiarity with observability and monitoring tools such as Prometheus, Grafana, ELK, or OpenTelemetry.

- Basic familiarity with Node.js or Java services.

- Exposure to AI/ML integrations within Python ecosystems.

- Working knowledge of Server OS environments of either Unix/Linux (RHEL 8/9/10) or Windows (Windows Server 2016/2019/2025).