AI DevOps Engineer

Role Summary

As an AI DevOps Engineer, you'll work across two connected areas: contributing to the reliability of our AI

agent systems, and helping build and maintain the infrastructure, pipelines, and cloud operations that keep our platforms running.

What You'll Do

AI Agent & Reliability Work

• Work on AI agent behavior: prompts, conversation flows, tool calling

• Build tests that replay realistic conversations and verify outcomes

• Investigate transcripts and logs to understand why interactions fail

• Debug and fix issues across the Python backend and, occasionally, the dashboard

Infrastructure & DevOps

• Build and maintain CI/CD pipelines for deployment across services

• Manage cloud infrastructure (provisioning, scaling, cost and security hygiene)

• Write and maintain infrastructure as code (Terraform, CloudFormation, or similar)

• Set up and improve monitoring, logging, and alerting across production systems

• Containerize services and manage orchestration (Docker, and container runtime environments)

• Support incident response: diagnose production issues and help drive fixes

• Continuously look for ways to automate manual operational work

What We're Looking For

• Solid Python skills and the ability to navigate an unfamiliar codebase

• Hands-on experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar)

• Working knowledge of cloud infrastructure (AWS, GCP, or Azure)

• Comfortable with containerization (Docker) and basic orchestration concepts

• Comfortable working with SQL and REST APIs

• Familiarity with Git and software testing

• Strong debugging and problem-solving skills across both application and infrastructure layers

• Curiosity and attention to detail: you verify what a system actually does rather than assuming it works as expected

Nice to Have

• Infrastructure as code experience (Terraform, Pulumi, CloudFormation)

• Experience with LLM APIs: prompting, function/tool calling, structured outputs

• Voice or real-time audio: LiveKit, Twilio, STT, TTS, WebRTC

• Kubernetes or other container orchestration

• Monitoring/observability tooling (Prometheus, Grafana, Datadog, or similar)

• Experience evaluating or testing LLM/agent behavior