Ai Systems Architect

Experteer Overview As AI Systems Architect, you will design and evolve an enterprise-scale Agentic AI platform to enable engineering teams to build, deploy, and operate production-ready AI agents securely and governably.You will shape reusable runtimes, governance, and developer experience to scale across the organization.The role emphasizes platform architecture, cross-functional collaboration, and driving enterprise adoption of AI best practices.You will work on high-impact problems at scale, enabling smarter decision making and faster innovation.Compensaciones / Beneficios - Architect a reusable enterprise Agentic AI platform (runtime, orchestration, context management, memory, evaluation, guardrails, observability) - Develop and maintain an Agent Harness with MCP integration - Define Golden Paths to standardize AI agent development and deployment - Build a model-agnostic AI runtime supporting multiple LLM providers and enterprise integrations - Collaborate with infrastructure teams on Kubernetes, GPU platforms, networking, and cloud-native AI infra - Establish enterprise AI governance (policy, security, prompt/model lifecycle, human-in-the-loop, evaluation, cost) - Integrate AI agents with enterprise platforms (CI/CD, ITSM, observability, cloud services, business apps) - Define engineering standards and mentor teams to drive enterprise adoption of Agentic AI practicesResponsabilidades - 5+ years designing cloud-native platforms or enterprise software architectures - Strong hands-on experience with Agentic AI architectures, orchestration, tool integration, memory, evaluation, and guardrails - Experience with agent frameworks such as LangGraph, CrewAI, Semantic Kernel, or AutoGen - Strong Python software engineering skills - Expertise in Kubernetes, containers, Infrastructure as Code, and cloud-native architectures - Understanding of AI infrastructure (GPUs, model serving, AI gateways, observability) - Experience designing developer platforms and reusable services - Professional proficiency in English and SpanishRequisitos principales - hybrid-friendly culture - Be Well programs (financial, mental, physical, social health) - career growth and personalized development goals - access to certifications with Microsoft, Google, and Amazon - coaching and hands-on experiences - supportive learning environment

platforms or enterprise software architectures - Strong hands-on experience with Agentic AI architectures, orchestration, tool integration, memory, evaluation, and guardrails - Experience with agent frameworks such as LangGraph, CrewAI, Semantic Kernel, or AutoGen - Strong Python software engineering skills - Expertise in Kubernetes, containers, Infrastructure as Code, and cloud-native architectures - Understanding of AI infrastructure (GPUs, model serving, AI gateways, observability) - Experience designing developer platforms and reusable services - Professional proficiency in English and SpanishRequisitos principales - hybrid-friendly culture - Be Well programs (financial, mental, physical, social health) - career growth and personalized development goals - access to certifications with Microsoft, Google, and Amazon - coaching and hands-on experiences - supportive learning environment