Staff AI-Native DevOps Engineer

Job summary

Own the build, deployment, and reliability of a conversational AI platform across SaaS environments, enabling secure and measurable delivery. The role covers CI/CD and GitOps, Kubernetes infrastructure, infrastructure as code, observability, incident response, and operational tooling for agent orchestration, MCP and A2A services, and caching. It also applies production engineering practices to LLM-powered services to improve deployment velocity and reliability.

Benefits

Qualifications

• At least 8 years of relevant professional engineering experience.
• At least 6 years deploying and operating containerized applications and distributed services in production.
• At least 4 years of hands-on experience with Kubernetes, cloud infrastructure, and infrastructure automation.
• Proficiency in Go, Python, Bash, or a similar programming or scripting language.
• Experience building production-grade automation and infrastructure tooling.
• Experience using AI-assisted development tools and validating, debugging, and safely integrating generated code.
• Working knowledge of LLMs, Generative AI, agentic architectures, and their operational considerations.
• Experience leading complex infrastructure initiatives and driving engineering practices across teams.

Responsibilities

• Deploy, scale, and operate distributed microservices in production Kubernetes environments.
• Design infrastructure automation using infrastructure as code and Kubernetes-native tooling.
• Build and maintain CI/CD pipelines, GitOps workflows, and release automation.
• Implement observability, monitoring, and incident response; perform root cause analysis and drive remediation.
• Architect and optimize secure, scalable, cost-efficient cloud infrastructure across public and private clouds.
• Improve deployment velocity and reliability for conversational AI services and platform components.

Skills

Industry

Relocation