AI DevOps Engineer

About the role

The AI DevOps Engineer will ensure the reliability of AI agent systems while building and maintaining the infrastructure, pipelines, and cloud operations that keep the platforms running. This role bridges AI behavior work and core DevOps responsibilities.

Key responsibilities

• Develop and test AI agent prompts, conversation flows, and tool calling, including building replay tests for realistic conversations.
• Investigate logs and transcripts to diagnose interaction failures and debug Python backend and dashboard issues.
• Design, implement, and maintain CI/CD pipelines for multi‑service deployments.
• Manage cloud resources (provisioning, scaling, cost, security) using IaC tools such as Terraform or CloudFormation.
• Containerize services, manage Docker environments, and support orchestration platforms.
• Set up monitoring, logging, and alerting; respond to production incidents and automate operational tasks.

Required profile

• Strong Python programming skills and ability to work in an unfamiliar codebase.
• Hands‑on experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins or similar).
• Working knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker).
• Familiarity with SQL, REST APIs, Git, and software testing.
• Excellent debugging and problem‑solving abilities across application and infrastructure layers.

Required skills

• Python
• CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
• Cloud services (AWS, GCP, Azure)
• Docker
• Infrastructure as Code (Terraform, CloudFormation, Pulumi)
• SQL
• REST APIs
• Git
• Monitoring tools (Prometheus, Grafana, Datadog)
• Kubernetes (nice to have)
• LLM APIs, prompting, function calling (nice to have)
• LiveKit, Twilio, STT, TTS, WebRTC (nice to have)