AI Engineer, Product Software

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 tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective.

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 Summary Equinix 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.

Responsibilities Design, build, deploy, and maintain LLM-powered agents and AI-driven applications

Integrate AI capabilities into existing software platforms to enhance functionality, automation, and user experience

Implement tool integration using Model Context Protocol (MCP) and agent-to-agent (A2A) communication patterns

Design and implement automated evaluation frameworks, quality gates, benchmarking processes, and release criteria for customer-facing AI agents

Establish guardrails, human-in-the-loop approval mechanisms, escalation workflows, and Responsible AI governance controls

Monitor and optimize agent quality, accuracy, latency, reliability, adoption, observability, and operational costs

Design, implement, and maintain Retrieval-Augmented Generation (RAG) architectures, vector databases, and knowledge engineering solutions

Troubleshoot agent failures and continuously improve agent performance through prompt engineering, context optimization, workflow orchestration, and evaluation feedback loops

Design, build, and manage automated CI/CD pipelines using Git Hub Actions (GHA) and modern Dev Ops practices

Collaborate with cross-functional teams to gather requirements, define technical solutions, and deliver exceptional customer experiences

Troubleshoot and resolve issues related to client interfaces, APIs, integrations, and end-user interactions

Provide hands-on leadership in software architecture, design, development, automation testing, deployment, and operational support

Drive architecture decisions and establish engineering standards for AI-powered platforms and services

Partner with product managers, architects, security teams, and engineering leaders to define technical strategy and execution plans

Evaluate emerging AI technologies, frameworks, tools, and industry best practices to drive innovation and continuous improvement

Provide technical estimates, identify risks, and contribute to roadmap planning, prioritization, and delivery execution

Qualifications

Bachelor’s degree in computer science, Software Engineering, Data ScienceA Master's degree or PhD is highly desirable6+ years of experience in the full software development life cycle, including coding standards, code reviews, version control, build processes, and testing6+ years of experience in software design, development, and algorithm related solutions5+ years of programming with Python or Java languages3+ years of experience in…