As a Staff AI Engineer at MontyCloud, you will design, build, and operate production\-grade agentic AI systems powering intelligent cloud operations at scale. This role focuses on developing scalable AI agents, orchestration pipelines, and cloud\-native AI infrastructure while contributing to engineering standards, reliability, and operational excellence across the platform. You will work at the intersection of AI, cloud infrastructure, and autonomous operations to deliver systems that are reliable, observable, secure, and production\-ready.
*Key Responsibilities**
**Engineering \& Delivery**
Architect, build, and operate production\-grade AI agents and multi\-agent systems for cloud management use cases
Design and own AI inference and orchestration pipelines optimized for scalability, latency, reliability, and cost efficiency
Build safety and reliability guardrails for autonomous AI systems operating on live cloud infrastructure
Develop human\-in\-the\-loop workflows, rollback strategies, scoped permissions, and audit mechanisms for AI\-driven operations
Collaborate with platform, infrastructure, and data engineering teams to embed AI\-native automation into cloud management workflows
**Standards \& Technical Quality**
Implement observability and monitoring for agentic systems, including agent tracing, MCP interaction auditing, output quality monitoring, and cost governance
Contribute to engineering standards for agentic design patterns, agentic AI architectures, MCP server and tool design, Prompt engineering, RAG and Graph\-RAG pipelines, LLMOps practices, and Foundation model integrations.
Conduct rigorous technical reviews of AI architectures, systems, and features to improve engineering quality and reliability
Document technical decisions, trade\-offs, and implementation patterns clearly for broader engineering adoption
**Innovation \& Opportunity Identification**
Identify opportunities where agentic AI can improve product capabilities or operational efficiency
Build proof\-of\-concepts and prototypes to validate technical feasibility and scalability
Evaluate emerging AI technologies, LLMs, multi\-modal models, and agentic frameworks for adoption suitability
Stay current with advancements in agentic AI, orchestration frameworks, and production AI engineering practices
*Desired Skills and RequirementsMust Have**
**Agentic AI \& Multi\-Agent Systems**
Production\-grade agentic AI system design and development
Agentic AI system design \& architecture \- Multi\-agent architectures and orchestration, Agent\-to\-agent communication, Agent memory and planning strategies, Tool integration and MCP server design
Agent orchestration frameworks \- LangGraph, Strands Agents, CrewAI, AutoGen, or equivalent agentic AI frameworks
**LLMOps \& AI Platform Engineering**
AI Governance \& Lifecycle Management \- Prompt versioning and governance, evaluation frameworks, regression detection
AI Observability \& Monitoring \- Output quality monitoring, Agent tracing and observability
AI Cost Management \- Cost governance for high\-scale AI workloads