Core Responsibilities:
- CI/CD Pipeline Management: Build and maintain CI/CD pipelines to facilitate efficient and reliable software delivery.
- DevOps Tooling: Envision, implement, and roll out cutting-edge DevOps tooling and automation to streamline development and deployment processes.
- Cloud Cost Optimization: Develop strategies and implement measures to optimize cloud costs while maintaining system performance and reliability.
- Incident Response: Practice sustainable incident response strategies and participate in peer reviews and postmortems to continuously improve system reliability.
- Infrastructure Management: Manage our multi-environment infrastructure deployed in AWS cloud, comprising dockerized microservices in AWS ECS & various data stores and queueing technologies.
- Automation: Leverage modern solutions like Terraform & Ansible to reduce manual efforts and increase efficiency.
- Cross-team Collaboration: Engage with multiple teams, the Engineering team and the Operations team to define and implement best practices to achieve operational excellence.
- Problem Solving: Troubleshoot and resolve complex technical issues, identifying root causes and implementing effective solutions.
- Continuous Improvement: Drive innovation and adopt best practices in development, architecture, and technology stack to promote organizational growth and success.
Qualifications/ Essential Skills/ Experience:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum of 4 years of proven experience as a DevOps Engineer or in a similar capacity.
- Strong understanding of Infrastructure as Code tools using AWS CloudFormation, Terraform, Ansible, Puppet, Chef, or an equivalent.
- Extensive experience with cloud computing concepts and utilizing major cloud service providers (e.g., AWS, GCP, Azure) to design and optimize cloud-based solutions.
- In-depth knowledge of Docker, with practical exposure to container networking, storage interfaces, orchestration, deployment, scaling, monitoring, and troubleshooting.
- Strong experience with monitoring and alerting tools such as Datadog, Grafana, Prometheus, or New Relic
- Functional knowledge of microservice architecture & hands-on experience with Kubernetes-based workload troubleshooting & best practices.
- Strong understanding of scripting languages like Bash, Python, etc.
- Hands-on experience in CI/CD with tools such as Jenkins, Github Actions, etc.
- Functional knowledge and understanding of SQL and NoSQL databases and experience in optimizing database performance at scale.
- Working knowledge of streaming and queueing systems such as Kafka and RabbitMQ, including configuration, setup, and management.
- Preferred: Previous experience in deploying and managing machine learning models and developing data pipelines.
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What We Do
Safe Security is a pioneer in the “Cybersecurity and Digital Business Risk Quantification” (CRQ) space. It helps organizations measure and mitigate enterprise-wide cyber risk in real-time using it’s ML Enabled API-First SAFE Platform by aggregating automated signals across people, process and technology, both for 1st & 3rd Party to dynamically predict the breach likelihood (SAFE Score) & $$ Value at Risk of an organization
Headquartered in Palo Alto, Safe Security has over 200 customers worldwide including multiple Fortune 500 companies averaging an NPS of 73 in 2020.
Backed by John Chambers and senior executives from Softbank, Sequoia, PayPal, SAP, and McKinsey & Co., it was also one of the Top Contributors to the National Vulnerability Database(NVD) of the U.S. Government in 2019 and the ATT&CK MITRE Contributor in 2020.
The company, since 2018, has also been working with MIT in joint research for the development of their SAFE Scoring Algorithm. Safe Security has received several awards including the Morgan Stanley CTO Innovation Award.
