Senior Devops & Backend Engineer | CTC Upto 25-30LPA

Senior AWS DevOps and Python Backend Engineer | Capitalmind

Job Summary

We are looking for a Senior AWS DevOps and Python Backend Engineer with strong expertise in AWS cloud infrastructure, DevOps practices, and production-grade Python backend development.

This is a hands-on engineering role requiring the ability to independently design, develop, deploy, and maintain scalable Python applications and REST APIs while managing cloud infrastructure, CI/CD pipelines, and automation.

The ideal candidate combines strong software engineering fundamentals with cloud infrastructure expertise, production troubleshooting capabilities, and practical experience using AI-assisted development tools.

Production-grade Python backend development is mandatory. Candidates with only Python scripting or infrastructure automation experience will not be considered.

Responsibilities

- Design, deploy, and manage secure, scalable, and highly available AWS infrastructure using EC2, S3, RDS, IAM, VPC, Lambda, CloudWatch, and related services.

- Build and maintain automated CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI/CD, or equivalent tools.

- Independently develop, test, deploy, and maintain production-grade Python backend applications and RESTful APIs using FastAPI, Flask, or Django.

- Design scalable backend architectures, business logic, microservices, and third-party API integrations.

- Manage containerized applications using Docker, Kubernetes (EKS), or ECS.

- Implement Infrastructure as Code (IaC) using Terraform or equivalent tools.

- Develop Python and Shell scripts to automate infrastructure provisioning, deployment, monitoring, and operational workflows.

- Design and optimize database interactions using PostgreSQL, MySQL, MongoDB, or DynamoDB.

- Implement API authentication, authorization, validation, error handling, logging, and performance optimization.

- Write unit and integration tests using Pytest or equivalent frameworks.

- Monitor application and infrastructure performance, troubleshoot production issues, and conduct root cause analysis.

- Implement cloud security, observability, reliability, and cost-optimization best practices.

- Leverage AI-assisted engineering tools such as Claude Code, ChatGPT, and OpenAI Codex for development, debugging, testing, and automation while ensuring production-quality code.

Qualifications

- Experience: 5–7 years of hands-on experience in DevOps, Cloud Engineering, Backend Engineering, or related roles.

- AWS Expertise: Strong practical knowledge of AWS infrastructure, cloud architecture, security, networking, and deployment.

- Python Backend Development: Mandatory experience independently building, testing, deploying, and maintaining production-grade Python applications and REST APIs.

- Python Frameworks: Strong proficiency in at least one backend framework: FastAPI, Flask, or Django.

- Programming Fundamentals: Strong understanding of Python, object-oriented programming, data structures, asynchronous programming, debugging, and performance optimization.

- CI/CD: Hands-on experience with Jenkins, GitHub Actions, GitLab CI/CD, or similar deployment automation tools.

- Containers & Infrastructure: Experience with Docker, Kubernetes (EKS) or ECS, and Terraform or equivalent IaC tools.

- Databases: Working knowledge of relational and NoSQL databases, including PostgreSQL, MySQL, MongoDB, or DynamoDB.

- Testing: Experience writing unit and integration tests using Pytest or similar frameworks.

- Production Engineering: Strong understanding of Linux, networking, Git, monitoring, incident management, and production troubleshooting.

- AI Tools: Practical experience using Claude Code, ChatGPT, Codex, or similar AI coding assistants.

- Ownership: Ability to independently design, build, deploy, troubleshoot, and maintain production-ready engineering systems.

Preferred Qualifications

- Experience with AWS serverless technologies such as Lambda and API Gateway.

- Knowledge of microservices, distributed systems, and event-driven architectures.

- Experience with Redis, Kafka, RabbitMQ, or other messaging technologies.

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

- Experience in application security, database optimization, and performance engineering.

- Hands-on experience building asynchronous Python services and scalable backend architectures.

Ideal Candidate

A hands-on engineer who combines strong AWS DevOps expertise with proven production-grade Python backend development experience.

The ideal candidate can independently manage cloud infrastructure, build scalable Python services and APIs, automate CI/CD workflows, troubleshoot production systems, and use AI-assisted engineering tools to deliver secure, reliable, and maintainable solutions.

Important