Senior DevOps Engineer

We are seeking an experienced Senior DevOps Engineer to design, implement, and maintain scalable infrastructure and automation systems that support our software development and deployment processes.

The ideal candidate will have strong e=xpertise in cloud platforms, CI/CD pipelines, infrastructure as code, and system reliability practices.

This role requires collaboration with development, security, and operations teams to improve system performance, reliability, and deployment efficiency.

Experience supporting AI or Voice AI infrastructure is a strong plus.

Design, implement, and maintain scalable cloud infrastructure.

Automate provisioning and configuration management using Infrastructure as Code (IaC).

Optimize infrastructure for performance, cost efficiency, and scalability.

Architect multi-region, highly available production environments.

Design and operate Kubernetes clusters handling high production traffic.

Lead capacity planning, node pool design, and autoscaling strategies.

Define infrastructure standards across staging, pre-production, and production.

Drive infrastructure reliability improvements based on production incidents.

Implement workload isolation strategies and resource governance policies.

Build and maintain CI/CD pipelines using tools such as Jenkins, GitLab, or GitHub.

Implement automated build, test, and deployment processes.

Support continuous integration and continuous delivery best practices.

Design progressive delivery strategies (blue-green, canary deployments).

Implement automated rollback and deployment validation mechanisms.

Define GitOps-based deployment workflows where applicable.

Enforce artifact integrity, pipeline security scanning, and policy controls.

Optimize pipelines for high deployment frequency and production safety.

Deploy and manage infrastructure on cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure.

Manage containerized applications using Docker and orchestration systems like Kubernetes.

Support infrastructure for real-time applications including voice or conversational AI services.

Operate Kubernetes clusters at production scale with thousands of pods.

Design autoscaling strategies using HPA/VPA and cluster autoscalers.

Implement advanced networking configurations for low-latency systems.

Optimize infrastructure for real-time, high-concurrency workloads.

Lead troubleshooting of distributed systems across multiple services.

Implement monitoring, logging, and alerting solutions.

Ensure high availability, system reliability, and incident response processes.

Perform root cause analysis and system optimization.

Define and manage SLIs, SLOs, and error budgets.

Own production incidents end-to-end, including postmortems.

Reduce alert fatigue by designing high-signal alerting strategies.

Implement distributed tracing and deep observability practices.

Drive reliability initiatives based on root cause analysis.

Establish on-call processes and reliability standards.

Minimum of 8 years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering.

Strong experience with Linux system administration.

Hands-on experience with Infrastructure as Code tools such as Terraform or CloudFormation.

Experience building and maintaining CI/CD pipelines.

Strong knowledge of containerization and orchestration technologies.

Experience with cloud platforms (AWS, Azure, or GCP).

Proficiency in scripting languages such as Python, Bash, or Go.

Experience with monitoring tools (Prometheus, Grafana, ELK stack, etc.).

Strong problem-solving and troubleshooting skills.

Nice to Have

Experience deploying or supporting Voice AI / conversational AI infrastructure.

Familiarity with real-time audio streaming or telephony platforms such as Twilio.

Experience working with AI platforms such as OpenAI or cloud-based speech services.

Understanding of low-latency systems used for voice, speech, or real-time communication platforms.