Senior DevOps Engineer / Site Reliability Engineer (AWS)

Profisea is an Israeli DevOps and Cloud company providing services across cloud infrastructure, GitOps, DevSecOps, and FinOps.

We are looking for a Senior DevOps Engineer with strong AWS expertise to design, build, and operate cloud infrastructure for international clients. Alongside core DevOps responsibilities, you will improve production reliability and actively use AI tools to accelerate engineering, troubleshooting, and automation.

Responsibilities:
Design, implement, and maintain scalable, secure AWS infrastructure.
Build and manage infrastructure as code using Terraform and configuration management tools.
Deploy and operate containerized applications using Docker and Kubernetes.
Develop and maintain CI/CD pipelines using Jenkins, ArgoCD, GitHub Actions, or similar tools.
Manage Linux environments and support databases, messaging systems, and cloud networking.
Deliver infrastructure migrations, performance improvements, and cloud cost optimization.
Improve production availability and resilience through monitoring, actionable alerting, capacity planning, and recovery procedures.
Investigate production incidents, perform root cause analysis, and implement changes to prevent recurring issues.
Define and track relevant reliability indicators and service objectives together with client teams.
Use AI assistants extensively in daily engineering: infrastructure code, scripts, pipeline configuration, troubleshooting, documentation, and technical research.
Build AI-assisted workflows that automate repetitive tasks, with appropriate validation, testing, and protection of client data.
Collaborate directly with clients, architects, and development teams to translate business requirements into technical solutions.

Requirements:
5+ years of DevOps engineering experience, including strong hands-on AWS expertise.
Strong knowledge of Linux, networking, and system administration.
Practical experience with Terraform, Docker, and Kubernetes.
Experience building and maintaining CI/CD pipelines.
Experience with monitoring and logging tools such as Prometheus, Grafana, ELK/EFK, or Graylog.
Working knowledge of SQL/NoSQL databases and messaging systems.
Proficiency in Python, Bash, Go, or another language for operational automation.
Experience troubleshooting production systems and improving their reliability, performance, and availability.
Regular, practical use of AI coding assistants and other AI tools, with the ability to explain specific workflows and benefits.
Ability to review and validate AI-generated code and configurations for correctness, security, and maintainability.