Design, develop, test, and maintain scalable backend services and enterprise applications using Python.
Build reusable, maintainable, and high-quality code following engineering best practices.
Develop APIs, microservices, event-driven services, and workflow automation solutions.
Participate in architecture discussions and contribute to technical design, code reviews, and engineering standards.
Optimize application performance, scalability, and maintainability.

Design and deploy applications in cloud environments such as AWS, Azure, or Google Cloud Platform (GCP).
Build and manage cloud-native services using containers, orchestration, serverless, and managed platform services.
Support infrastructure automation using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or equivalent.
Ensure applications are designed for high availability, resiliency, scalability, and security in the cloud.

Operations / DevOps / Reliability :

Own production deployments, release engineering, monitoring, alerting, and operational support.
Implement and improve CI/CD pipelines for automated build, test, deployment, and rollback processes.
Troubleshoot production issues, perform root cause analysis, and drive long-term fixes.
Improve observability through logging, metrics, tracing, and dashboards.
Partner with operations, platform, and security teams to ensure reliable and compliant systems.
Drive operational excellence through automation, incident response readiness, and runbook creation.

Collaboration &

Leadership :
Work closely with product managers, architects, QA, DevOps, and business stakeholders to deliver high-impact solutions.
Mentor junior engineers and promote best practices in coding, cloud engineering, and operational support.
Contribute to Agile ceremonies including sprint planning, estimation, retrospectives, and technical backlog grooming.
Lead technical initiatives and influence engineering decisions across teams.

Bachelors or Masters degree in Computer Science, Engineering, or related field.
6 years of software engineering experience, with strong hands-on development expertise in Python.
Strong experience building backend systems, APIs, distributed applications, or microservices.
Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
Experience with containerization tools such as Docker and orchestration platforms like Kubernetes.
Experience with CI/CD pipelines, source control, and release automation tools such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
Experience supporting applications in production, including monitoring, alerting, incident troubleshooting, and performance optimization.
Strong understanding of software design principles, clean architecture, testing frameworks, and secure coding practices.
Familiarity with relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, DynamoDB, etc.
Strong problem-solving, communication, and cross-functional collaboration skills.

Experience with DevOps, Site Reliability Engineering (SRE), or platform engineering practices.
Experience with Terraform, Ansible, or other automation/IaC tools.
Familiarity with message queues and streaming platforms such as Kafka, RabbitMQ, or Pub/Sub.
Experience with observability tools such as Prometheus, Grafana, Datadog, Splunk, ELK, or OpenTelemetry.
Knowledge of cloud security, IAM, secrets management, and policy compliance.
Experience working in enterprise environments with high availability and compliance requirements.
Exposure to AI/ML platforms, data pipelines, or intelligent automation is a plus.

- Programming : Python, Shell scripting, SQL

- Cloud : AWS / Azure / GCP

- DevOps &

- Containers &

- IaC &

- APIs &

- Databases : PostgreSQL, MySQL, MongoDB, Redis

- Tools : Git, Jenkins, GitHub Actions, Azure DevOps, Prometheus, Grafana, ELK, Datadog

Python Developer

Related