Principal Cloud Engineer

**Who are we?**

Equinix is the world’s digital infrastructure company®, 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 Summary**

We’re looking for a Principal Cloud Engineer with a strong foundation in Multi-Cloud & multi region deployment, 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**

Cloud Architecture & Engineering
- Deep expertise in designing, implementing, and managing architectures across multiple cloud platforms (e.g., AWS, Azure, GCP)
- Proven experience in architecting hybrid and multi-cloud solutions, including interconnectivity, security, workload placement, and DR strategies
- Strong knowledge of cloud-native services (e.g., serverless, containers, managed databases, storage, networking)
- Experience with enterprise-grade IAM, security controls, and compliance frameworks across cloud environments

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

Automation, IaC, CI/CD
- Mastery of Infrastructure as Code (IaC) tools — especially Terraform, Terragrunt, and CloudFormation / ARM / Deployment Manager
- Experience building and managing cloud automation frameworks (e.g., using Python, Go, or Bash for orchestration and tooling)
- Hands-on experience with CI/CD pipelines (e.g., GitHub Actions) for cloud resource deployments
- Expertise in implementing policy-as-code & Compliance-as-code (e.g., Open Policy Agent, Sentinel)

Security, Governance & Cost
- Strong background in implementing cloud security best practices (network segmentation, encryption, secrets management, key management, etc.).
- Experience with multi-account / multi-subscription / multi-project governance models, including landing zones, service control policies, and organizational structures
- Ability to design for cost optimization, tagging strategies, and usage monitoring across cloud providers

Monitoring & Operations
- Familiarity with cloud monitoring, logging, and observability tools (e.g., CloudWatch, Azure Monitor, GCP Operations Suite, Datadog, Prometheus)
- Experience with incident management and building self-healing cloud architectures

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

Leadership & Collaboration
- Experience leading cloud architecture reviews, defining standards, and mentor