DevOps Engineer

Technical Infrastructure:

• Cloud & Infrastructure: AWS EC2, Terraform Enterprise, Docker, Aurora, Mesos, Kubernetes, ELK (Elastic Search, Logstash & Kibana).
• Observability & Automation: Grafana, Prometheus, Datadog, Telegraf, Runscope, Apollo, GraphQL.
• Development Stack: Microservices architecture, Spring, Java & NodeJS, React, Express.js.
• Data & Storage: Amazon RDS, Dynamo DB, Postgres, Oracle, MySQL, Influx DB, Linux, Jenkins, GitHub.
• AI & Agentic Automation: AWS Bedrock LLMsandAWS Bedrock Engineerfor building and integrating scalable, low-latency AI-driven automation capabilities.
• You can read more on our Engineering Blog -

About the role:

You will constantly be asking, what are the most important infrastructure problems we need to solve for today, that will increase the reliability and performance of our applications and infrastructure.

• Identify and solve the most critical infrastructure challenges to improve system reliability, scalability, and performance.
• Design, test, and implement AI-enhanced DevOps workflows, including autonomous agents for monitoring, remediation, and optimization.
• Partner with SRE and development teams to build robust, self-service deployment pipelines and infrastructure tooling.
• Evaluate new technologies to continuously improve system automation, cost efficiency, and security.
• Work with AI-enhanced monitoring and self-healing infrastructure components powered by agentic patterns.

Key Responsibilities:

• Build, maintain, and evolve cloud infrastructure with Infrastructure as Code (Terraform, CloudFormation).
• Manage containerized workloads (Docker, Kubernetes) at scale, with a focus on extending capabilities through AI-driven orchestration.
• Implement and maintain advanced monitoring, observability, and alerting systems enhanced with agent-based analytics.
• Automate workflows to reduce manual intervention and accelerate delivery cycles.
• Collaborate with cross-functional teams to ensure infrastructure meets the needs of high-availability, low-latency applications.
• Regularly review and optimize existing architecture for cost, security, and performance improvements.

Skills and Experience

• 3 to 5 years of hands-on SRE/DevOps experience in Agile environments
• Strong AWS experience in a production setting.
• Strong knowledge and skills of AI-enhanced DevOps workflows and agentic infrastructure models.
• Proficiency in diagnosing outages and restoring service with urgency.
• Infrastructure as Code expertise (Terraform, CloudFormation).
• Experience with containerization (Docker, Kubernetes).
• Familiarity with CI/CD tools, scripting languages, and observability platforms.
• Strong collaboration skills, with the ability to influence and guide best practices

Preferred Skills and Interests:

• RDBMS expertise and Linux fluency
• Event-driven systems and message queue management
• Security, including firewalls, load balancing, secret management