Principal Engineer - AI Engineering

MontyCloud Principal Engineer - AI Engineering 12 - 14 YOE MontyCloud Bangalore Office Full-Time Role OverviewAs a Principal AI Engineer at MontyCloud, you will define and drive the technical vision for agentic AI systems powering the next generation of intelligent cloud operations. This role focuses on architecting scalable, production-grade AI systems, establishing engineering standards, mentoring senior engineers, and leading strategic technical initiatives across the organization. You will work at the intersection of AI, cloud infrastructure, and autonomous operations to build systems that are reliable, observable, and capable of operating at enterprise scale.Key ResponsibilitiesTechnical Leadership & ArchitectureDefine and own the technical vision for agentic AI systems across the platformArchitect scalable multi-agent systems, orchestration frameworks, MCP server infrastructure, retrieval and memory pipelines, and observability layersDrive architectural decisions related to MCP/ tool ecosystems, AI platform design, and LLMOps infrastructureEvaluate emerging AI technologies, frameworks, and models to influence engineering and product roadmapsCreate and maintain Architecture Decision Records (ADRs) and technical standardsEngineering & DeliveryDesign and develop critical AI platform components and infrastructureEstablish AI engineering best practices and discipline across the organisation - design patterns, evaluation practices, prompt engineering, reliability standards, governance, and cost optimizationLead cross-functional technical initiatives to improve AI system quality, reliability and scalabilityCollaborate with platform, infrastructure, and data engineering teams to embed AI-driven automation into cloud operations workflowsMentorship & Technical CommunityMentor Lead and Staff AI Engineers through architecture reviews, design discussions, and problem-solving sessionsConduct rigorous technical reviews of designs, architectures, and major code contributionsContribute to MontyCloud’s technical brand through technical writing, open-source contributions, or speaking engagementsInnovation & Strategic ImpactIdentify opportunities where agentic AI can create significant product or operational improvementsBuild prototypes, technical proposals, and proof-of-concepts to validate new ideasStay current with advancements in AI research, agentic frameworks, and LLMOps practicesDesired Skills and RequirementsMust HaveAgentic AI & Multi-Agent SystemsProduction-grade agentic AI system design and developmentAgentic AI System Design & Architecture - Multi-agent architectures and orchestration, Agent-to-agent communication, Agent memory and planning strategies, Tool integration and MCP server designAgent orchestration frameworks - LangGraph, Strands Agents, CrewAI, AutoGen, or equivalent agentic AI frameworksLLMOps & AI Platform EngineeringAI Governance & Lifecycle Management - Prompt versioning and governance, evaluation frameworks, regression detectionAI Observability & Monitoring - Output quality monitoring, Agent tracing and observabilityAI Cost Management - Cost governance for high-scale AI workloadsCloud & InfrastructureCloud AI Platforms & Services - AWS cloud ecosystem, AWS Bedrock, AgentCoreCloud-Native Infrastructure & Deployment - Cloud-native AI deployments, Kubernetes, DockerInfrastructure as Code (IaC) - TerraformFoundation Models & AI IntegrationsFoundation model API integration - OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Hugging FaceMCP and AI tool integration architectureRAG & Knowledge SystemsRetrieval-Augmented Generation (RAG) and Graph-RAG architecturesEmbedding strategies, retrieval and reranking systemsKnowledge graph integrationsTechnical Leadership and CommunicationCross-team technical influenceTechnical communication and documentationOrganization-level engineering ownershipProactive problem identification and resolutionGood to HaveDomain Experience AI...