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Staff Engineer, Product Software
Equinix, Inc · Bangalore, India · Brasil
Publicada em 30/09/2026
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Who are we?Equinix is the world's digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.Help us challenge assumptions, uncover bias, and remove barriers-because progress starts with fresh ideas. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work.Job SummaryEquinix is seeking a highly experienced and hands-on engineering professional to drive the development, and delivery of next-generation AI-powered platforms and customer-facing agentic solutions. This role combines software engineering excellence with deep expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and modern cloud-native development practices.The ideal candidate will lead the design and implementation of AI agents, establish engineering best practices, define quality and governance frameworks, and collaborate closely with product, architecture, security, and engineering teams to deliver scalable, secure, and reliable AI solutions that enhance customer experiences and business outcomes.ResponsibilitiesDesign, build, deploy, and maintain LLM-powered agents and AI-driven applicationsIntegrate AI capabilities into existing software platforms to enhance functionality, automation, and user experienceImplement tool integration using Model Context Protocol (MCP) and agent-to-agent (A2A) communication patternsDesign and implement automated evaluation frameworks, quality gates, benchmarking processes, and release criteria for customer-facing AI agentsEstablish guardrails, human-in-the-loop approval mechanisms, escalation workflows, and Responsible AI governance controlsMonitor and optimize agent quality, accuracy, latency, reliability, adoption, observability, and operat
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