Platform Engineer

**Platform Engineer**:

- JR-154938
- Hybrid
- Singapore
- Information Technology
- Full time

**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.

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**

We’re looking for a 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.

**Responsibilities**

Platform & Cloud Engineering
- Develop and maintain real-time and batch data pipelines using tools like Airflow, dbt, Dataform, and Dataflow/Spark
- Design and develop event-driven architectures using Apache Kafka, Google Pub/Sub, or equivalent messaging systems
- Architect and manage multi-cloud and hybrid cloud platforms (e.g., GCP, AWS, Azure) optimized for AI, ML, and real-time data processing workloads
- Build reusable frameworks and infrastructure-as-code (IaC) using Terraform, Kubernetes, and CI/CD to drive self-service and automation
- Ensure platform scalability, resilience, and cost efficiency through modern practices like GitOps, observability, and chaos engineering

Data Architecture & Governance
- Lead initiatives in data modeling, semantic layer design, and data cataloging, ensuring data quality and discoverability across domains
- Implement enterprise-wide data governance practices, schema enforcement, and lineage tracking using tools like DataHub, Amundsen, or Collibra
- Guide adoption of data fabric and mesh principles for federated ownership, scalable architecture, and domain-driven data product development

AI & GenAI Platform Integration
- Integrate LLM APIs (OpenAI, Gemini, Claude, etc.) into platform workflows for intelligent automation and enhanced user experience
- Build and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, or AutoGen for use cases such as pipeline debugging, code generation, and MLOps
- 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 datasets

Engineering Enablement
- Create extensible CLIs, SDKs, and blueprints to simplify onboarding, accelerate development, and standardize best practices
- Streamline onboarding, documentation, and platform implementation & support using GenAI and conversational interfaces
- Collaborate across teams to enforce cost, reliability, and security standards within platform blueprints
- Work with engineering by introducing platform enhancements, observability, and cost optimization techniques
- Foster a culture of ownership, continuous learning, and innovation

**Qualifications**
- 5+ years of hands-on experience in Platform or Data Engineering, Cloud Architecture, AI Engineering roles
- Strong programming background in Java, Python, SQL, and one or more general-purpose languages
- Deep knowledge of data modeling, distributed systems, and API design in production environments
- Proficiency 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 Platform
- Proven experience building scalable, efficient data pipelines for structured and unstructured data
- Experience with GenAI/LLM frameworks and tools for orchestration and workflow automation
- Experience with RAG pipelines, vector databases, and embedding-based search
- Familiarity with observability tools (Prometheus, Grafana, OpenTelemetry) and strong debugging skills across the stack
- Experience with ML Platforms (MLFlow, Vertex AI, Kubeflow) and AI/ML observability tools
- Prior implementation of data mesh or data fabric in a large-scale enterprise
- Experience with Looker Modeler, LookML, or semantic modeling layers

Why You’ll Love This Role
- Drive technical leadership across AI-native data platforms, automation systems, and self-service tools
- Collaborate across teams to shape the next generation of intelligent platforms in the enterprise
- Work with a high-energy, mission-driven team that embraces innovation, open-source, and experimentation

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualifie