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Backend Software Engineer II
3 months ago
The Managed Services Engineering team is responsible for developing and maintaining the applications, tools, and services the service delivery teams use for our Managed Detection & Response, Vulnerability Management, Application Security, and Incident Response.
Our applications are built using an agile software development approach with an emphasis on implementing DevOps best practices. Cloud infrastructure is built on AWS using many of its popular services such as ECS, API Gateway, Load Balancing, EC2, SQS, SNS, Event Bridge, IAM, RDS, etc, with the architecture provisioned and updated using Terraform. Application and service back-ends are primarily written in Python (Django, Django Rest Framework, Flask) with front-ends learning heavily on Javascript ES6 and React.
About the Role:Rapid7 is looking for a Software Engineer II to support Rapid7's 24x7 Managed Services and Incident Response (IR) teams. We are looking for people who thrive off delivering practical solutions for the problems of today, iterating on existing solutions, and proactively prototyping to head off the security problems of tomorrow. This team is a true force multiplier for front-line security practitioners, unveiling new capabilities and automating any repetitive actions to dramatically enhance their quality of life and optimize their actions. Success in this role will require strong communication skills and an unwavering sense of self-accountability.
Requirements:AWS:
- Lambda
- S3
- SQS
- SNS
Other Tools:
- Python
- Django/DRF experience preferred
- Docker
Nice to Have:
- Terraform
- AWS VPC
- AWS RDS
- AWS Opensearch
- AWS EventBridge
- Plan, build, deploy, maintain, and monitor highly available services and tools the Managed Services team uses for service delivery.
- Work cross-functionally with other product engineering teams
- Github code reviews
Must be familiar with or driven to learn how to build and deploy software as services on cloud infrastructure.
Skills and Tools used in Daily Workflow:
- Planning:
- Jira, Confluence, and Agile methodologies
- Development:
- Microservice architectures, Legacy Codebases, Django, React, Fast API, Flask
- Cloud Architecture - AWS (ECS, S3, IAM, API Gateway, SQS, SNS, Event Bridge, etc)
- API-first, scripts/CLI tools, web applications
- Data Relevance: Tools and Services to enable self service of Analysts
- Deployed at a high cadence (DevOps):
- CI/CD: Github -> Jenkins (Chef, Saltstack, Ansible, Puppet experience also works)
- IAC: Terraform
- Tested Practically:
- Unit, End to End