Software Development Engineer III - DevOps Engineer
Quick Summary
Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified,
Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified, and real-time view of their security posture. We don’t just provide data; we provide certainty.
We are a $170M Series C-funded category leader. We don’t play in the mid-market; we operate at the highest levels of global enterprise. Today, we are proud to serve 10% of the Fortune 500, protecting global icons such as Apple, Netflix, AT&T, Verizon, and Victoria’s Secret.
As we scale toward our next chapter, we are looking for high-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity.
Safe is not a typical corporate environment. We are a high-intensity, mission-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence.
What We Offer
~3 min readAs a Senior DevOps Engineer, you will play a critical role in designing, implementing, and maintaining secure and scalable infrastructure while driving automation initiatives to improve system observability, availability, reliability, and performance. You will lead efforts in infrastructure provisioning, capacity planning, and CI/CD pipeline management, ensuring the seamless delivery of our services.
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.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Minimum of 5+ 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.
Preferred: Previous experience in deploying and managing machine learning models and developing data pipelines.
Familiarity with Kafka, RabbitMQ, Redis, and other distributed infrastructure components.
Strong hands-on experience in AWS cloud infrastructure (Professional Certification preferred)
Strong hands-on expertise in Kubernetes (EKS preferred) with a deep understanding of cluster architecture, networking, autoscaling, scheduling, ingress controllers, and storage management.
Location & Eligibility
Listing Details
- Posted
- May 28, 2026
- First seen
- May 28, 2026
- Last seen
- May 28, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- May 28, 2026
Signal breakdown
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