Senior Platform Engineer – Data & AI
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Senior Platform Engineer – Data & AI
- JR-160546
- Hybrydowy
- Toronto
- 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.
Job Summary
We are seeking a highly skilled Senior Platform Engineer – Data & AI to architect and build next-generation AI-native and Agentic platforms that power enterprise-scale data, automation, and intelligent systems.
This role goes beyond traditional data platforms to focus on Agentic AI ecosystems, including multi-agent orchestration, agent lifecycle management, agent communication protocols, and AI-driven platform automation.
You will design and operate a unified platform that supports:
Data pipelines and real-time streaming
APIs and microservices
GenAI and LLM-powered applications
Agentic workflows and multi-agent systems
Working closely with AI/ML engineers, platform teams, SRE, and product teams, you will help build a scalable, observable, and governed AI platform on Google Cloud, leveraging automation, IaC, and modern cloud-native patterns.
Responsibilities
Platform & Cloud Engineering
Architect and build cloud-native platforms on Google Cloud (GCP) supporting data, AI, and agentic workloads
Design event-driven architectures using Apache Kafka, Google Pub/Sub, or equivalent systems
Build scalable microservices and APIs using modern frameworks (e.g., Java, Spring Boot)
Develop and manage real-time and batch data pipelines using Airflow, Dataform, Dataflow, Spark, or similar tools
Implement Infrastructure-as-Code (IaC) using Terraform and Kubernetes for scalable, repeatable deployments
Enable platform automation using CI/CD, GitOps, and self-service frameworks
Ensure platform scalability, reliability, and cost efficiency
Agentic Platform & Multi-Agent Systems
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Design and build Agentic Platforms that support:
Agent lifecycle management
Task orchestration
Context and memory handling
Develop and orchestrate multi-agent systems using frameworks such as CrewAI, LangGraph, AutoGen, or equivalent
Implement agent communication and coordination patterns across distributed systems
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Build and integrate:
Agent Gateway for managing agent interactions and routing
A2A (Agent-to-Agent) communication protocols
MCP (Model Context Protocol) or equivalent for context sharing and orchestration
ADK (Agent Development Kits) or internal frameworks for rapid agent development
Enable use cases such as:
Autonomous pipeline monitoring and remediation
AI-assisted platform operations
Intelligent workflow automation
Code and data pipeline generation
AI & GenAI Platform Engineering
Integrate LLMs and GenAI services (e.g., OpenAI, Gemini, Claude) into platform workflows.
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Build and support:
RAG pipelines and retrieval systems
Vector search and embedding architectures (Weaviate, Pinecone, FAISS)
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Enable AI-driven automation for:
Platform operations
Data quality monitoring
Incident analysis and resolution
Develop reusable AI platform services and APIs for enterprise consumption.
Agent Observability & AI Operations
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Design and implement Agent Observability frameworks, including:
Agent execution tracing
Decision tracking and explainability
Latency and performance monitoring
Failure and retry analysis
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Integrate observability using tools like:
OpenTelemetry, Prometheus, Grafana
AI/LLM observability tools (e.g., prompt tracing, evaluation frameworks)
Enable end-to-end observability across data pipelines, APIs, and agent workflows.
Data Architecture & Governance
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Lead initiatives in:
Data modeling and semantic layer design
Data cataloging and metadata management
Data quality and lineage tracking
Implement governance frameworks using tools such as DataHub, Collibra, or equivalent.
Support data mesh and data fabric architectures for federated data ownership.
Automation & Intelligent Platform Operations
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Build automation-first platforms leveraging:
AI-driven workflows
Self-healing systems
Event-driven automation
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Use GenAI to:
Automate operational tasks
Generate platform configurations and code
Enhance developer productivity
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Collaborate with SRE and Production Support teams to improve:
Reliability
Incident response
Operational efficiency
Engineering Enablement
Develop platform SDKs, CLIs, and reusable blueprints.
Enable self-service platform capabilities for engineering teams.
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Standardize best practices for:
APIs
Data pipelines
Agent development
Mentor engineers and promote a culture of innovation and continuous learning.
Qualifications
Experience
8–12 years of experience in Platform Engineering, Data Engineering, Cloud Architecture, or AI Platform Engineering
Proven experience building enterprise-scale data and AI platforms
Core Technical Skills
Strong programming expertise in Java, Python, Full-Stack and SQL
Experience building microservices and API-driven architectures
Deep understanding of distributed systems and cloud-native design
Cloud & Platform Engineering
Strong experience with Google Cloud Platform (GCP) (mandatory)
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Hands-on experience with:
Kubernetes and containerized workloads
Terraform and Infrastructure-as-Code
CI/CD pipelines and GitOps
Streaming & Data Systems
Experience with Kafka, Pub/Sub, Spark, Flink, or similar systems
Strong background in real-time and batch data processing
AI, GenAI & Agentic Systems
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Hands-on experience with:
LLM frameworks and APIs
Multi-agent orchestration frameworks (CrewAI, LangGraph, AutoGen, etc.)
RAG pipelines and vector databases
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Experience building or working with:
Agent Gateway architectures
A2A communication models
MCP or context-sharing frameworks
Agent Development Kits (ADKs)
Full Stack & UI Development
Experience building full stack applications with modern frontend frameworks (React, Angular, Vue.js).
Strong understanding of REST/GraphQL APIs and UI integration patterns.
Experience with real-time UI updates using WebSockets or streaming architectures.
Familiarity with design systems, UX principles, and responsive design.
Experience building platform dashboards, developer portals, or observability UIs.
Observability & Reliability
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Experience with observability tools:
Prometheus, Grafana, OpenTelemetry
Strong debugging and system analysis skills.
Familiarity with AI/LLM observability and evaluation frameworks.
Data Governance & Architecture
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Experience with:
Data catalogs and metadata platforms
Data quality and lineage frameworks
Semantic modeling and data governance
Preferred Qualifications
Experience with Vertex AI, MLflow, Kubeflow, or ML platforms.
Prior implementation of data mesh or data fabric architectures.
Experience with Looker Modeler / LookML or semantic layers.
Exposure to AI safety, governance, and responsible AI practices.
Experience building enterprise AI/Agentic platforms at scale.
Why You’ll Love This Role
Work on cutting-edge Agentic AI and multi-agent systems
Build AI-native enterprise platforms at scale
Drive innovation in automation, GenAI, and intelligent systems
Collaborate with high-impact teams across data, AI, and platform engineering
Shape the future of AI-driven enterprise architecture
The targeted pay range for this position in the following location is / locations are:
Canada - Toronto Office TRO : 131,000 - 181,000 CAD / Annual
Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location.The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.
The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.
Equinix Benefits
As an employee, you become important to Equinix’s success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we’re providing you with the best package possible. So, wherever you are in your career and life, you’ll be able to enhance your experience and bring your whole self to work.
Employee Assistance Program: An Employee Assistance program is available to all employees.
Canada Core Benefits: - Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members. - Retirement: You may also enroll in Equinix-sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax-Free Savings Plan (TSFA). - Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.Equinix 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 this form.
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.
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This posting is a new position within our organization.