DevOps Engineer AI Systems Development (Contract)

What You Will Do

• Design, develop, and maintain AI-enabled systems, tools, and engineering workflows.
• Use Python to build automation, APIs, services, integrations, and AI tooling.
• Work extensively with AI development platforms and tools, including Claude or similar AI coding/development environments.
• Build and integrate AI workflows involving prompts, agents, tools, plugins, MCP servers, and related components.
• Develop systems that enable AI tools to interact with APIs, services, data, and engineering environments.
• Debug and troubleshoot AI-generated code and AI-driven workflows.
• Work with SRE and DevOps teams to deploy, operate, monitor, and troubleshoot AI systems.
• Use Kubernetes and container-based environments for deployment and operations.
• Implement basic observability using tools such as Grafana and Prometheus.
• Participate in technical design, code reviews, troubleshooting, and continuous improvement.
• Translate engineering requirements into practical AI-enabled tools and solutions.

Required Qualifications

• 5 years+ overall software/DevOps engineering experience.
• Strong hands-on Python programming experience.
• Strong practical experience building AI/GenAI-powered systems or developer tools.
• Hands-on experience using AI coding/development tools such as Claude, GitHub Copilot, or equivalent platforms.
• Experience using AI for software development, automation, debugging, or engineering workflows for approximately 1 year or more.
• Understanding of AI agents, LLM-based workflows, prompt engineering, tool calling, and AI orchestration.
• Familiarity with MCP servers, plugins, skill files, or similar AI extensibility concepts.
• Good understanding of DevOps fundamentals, including CI/CD, containers, deployment, and troubleshooting.
• Basic to intermediate Kubernetes knowledge.
• Exposure to Grafana and Prometheus or similar observability tools.
• Strong debugging and problem-solving abilities, particularly around AI-generated code and AI system failures.
• Ability to work closely with SRE, software engineering, and AI/ML teams.
• Strong communication and collaboration skills.

Preferred Qualifications

• Experience with FastAPI or similar Python web frameworks.
• Experience building AI agents, AI assistants, internal developer tools, or AI-powered automation.
• Experience integrating LLMs with APIs, databases, services, or enterprise systems.
• Experience with MCP-based architectures or similar AI tool-integration frameworks.
• Experience with Kubernetes-based AI/ML or application deployments.
• Exposure to cloud platforms and cloud-native architectures.
• Experience with monitoring, logging, alerting, and production troubleshooting.
• Experience working in an environment where AI is actively used for software engineering and system development.