Job Description

Who are we?Equinix is the worlds digital infrastructure companyxc2xae, operating over 260 data centers across the globe. Digital leaders harness Equinix's trusted platform to bring together and interconnect foundational infrastructure at software speed. Equinix enables organizations to access all the right places, partners and possibilities to scale with agility, speed the launch of digital services, deliver world-class experiences and multiply their value, while supporting their sustainability goals.Our culture is based on collaboration and the growth and development of our teams. We hire hardworking people who thrive on solving challenging problems and give them opportunities to hone new skills and try new approaches, as we grow our product portfolio with new software and network architecture solutions. We embrace diversity in thought and contribution and are committed to providing an equitable work environment that is foundational to our core values as a company and is vital to our success.Job SummaryWere looking for a Senior Platform Engineer with a strong foundation in data architecture, distributed systems, and modern cloud-native platforms to architect, build, and maintain intelligent infrastructure and systems that power our AI, GenAI and data-intensive workloads.Youll work closely with cross-functional teams, including data scientists, ML & software engineers, and product managers & play a key role in designing a highly scalable platform to manage the lifecycle of data pipelines, APIs, real-time streaming, and agentic GenAI workflows, while enabling federated data architectures. The ideal candidate will have a strong background in building and maintaining scalable AI & Data Platform, optimizing workflows, and ensuring the reliability and performance of Data Platform systems.ResponsibilitiesPlatform & Cloud EngineeringDevelop and maintain real-time and batch data pipelines using tools like Airflow, dbt, Dataform, and Dataflow/SparkDesign and develop event-driven architectures using Apache Kafka, Google Pub/Sub, or equivalent messaging systemsBuild and expose high-performance data APIs and microservices to support downstream applications, ML workflows, and GenAI agentsArchitect and manage multi-cloud and hybrid cloud platforms (e.g., GCP, AWS, Azure) optimized for AI, ML, and real-time data processing workloadsBuild reusable frameworks and infrastructure-as-code (IaC) using Terraform, Kubernetes, and CI/CD to drive self-service and automationEnsure platform scalability, resilience, and cost efficiency through modern practices like GitOps, observability, and chaos engineeringData Architecture & GovernanceLead initiatives in data modeling, semantic layer design, and data cataloging, ensuring data quality and discoverability across domainsImplement enterprise-wide data governance practices, schema enforcement, and lineage tracking using tools like DataHub, Amundsen, or CollibraGuide adoption of data fabric and mesh principles for federated ownership, scalable architecture, and domain-driven data product developmentAI & GenAI Platform IntegrationIntegrate LLM APIs (OpenAI, Gemini, Claude, etc.) into platform workflows for intelligent automation and enhanced user experienceBuild and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, or AutoGen for use cases such as pipeline debugging, code generation, and MLOpsExperience in developing and integrating GenAI applications using MCP and orchestration of LLM-powered workflows (e.g., summarization, document Q&A, chatbot assistants, and intelligent data exploration)Hands-on expertise building and optimizing vector search and RAG pipelines using tools like Weaviate, Pinecone, or FAISS to support embedding-based retrieval and real-time semantic search across structured and unstructured datasetsEngineering EnablementCreate extensible CLIs, SDKs, and blueprints to simplify onboarding, accelerate development, and standardize best practicesStreamline onboarding, documentation, and platform implementation & support using GenAI and conversational interfacesCollaborate across teams to enforce cost, reliability, and security standards within platform blueprints.Work with engineering by introducing platform enhancements, observability, and cost optimization techniquesFoster a culture of ownership, continuous learning, and innovationQualifications5+ years of hands-on experience in Platform or Data Engineering, Cloud Architecture, AI Engineering rolesStrong programming background in Java, Python, SQL, and one or more general-purpose languagesDeep knowledge of data modeling, distributed systems, and API design in production environmentsProficiency in designing and managing Kubernetes, serverless workloads, and streaming systems (Kafka, Pub/Sub, Flink, Spark)Experience with metadata management, data catalogs, data quality enforcement, and semantic modeling & automated integration with Data PlatformProven experience building scalable, efficient data pipelines for structured and unstructured dataExperience with GenAI/LLM frameworks and tools for orchestration and workflow automationExperience with RAG pipelines, vector databases, and embedding-based searchFamiliarity with observability tools (Prometheus, Grafana, OpenTelemetry) and strong debugging skills across the stackExperience with ML Platforms (MLFlow, Vertex AI, Kubeflow) and AI/ML observability toolsPrior implementation of data mesh or data fabric in a large-scale enterpriseExperience with Looker Modeler, LookML, or semantic modeling layersWhy Youll Love This RoleDrive technical leadership across AI-native data platforms, automation systems, and self-service toolsCollaborate across teams to shape the next generation of intelligent platforms in the enterpriseWork with a high-energy, mission-driven team that embraces innovation, open-source, and experimentationEquinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing .Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

Equinix