Backend / Platform Engineer

Jobgether; Canada; Remote; CAD 90,000 - 150,000; Full time

Benefits offered by this job

Fully remote

Job summary

Partner Company is seeking a Backend / Platform Engineer based in Canada to design, develop, and operate core backend services for an enterprise AI platform. You will build scalable APIs, orchestration layers, and platform infrastructure in a remote-first environment, taking ownership of services throughout their lifecycle.

You will collaborate with cross-functional teams to implement entitlements, tenancy models, metering, quotas, and secure data access while addressing reliability, security,

Qualifications

• Proven experience designing and operating production backend systems and APIs.
• Strong fundamentals to build reliable, scalable, and maintainable applications.
• Familiarity with multi-tenant architectures and API gateways.

Responsibilities

• Design, develop, and operate core backend services powering an enterprise AI platform.
• Build platform capabilities such as entitlements, tenancy, usage metering, quotas, and data access controls.
• Develop scalable APIs and developer experiences for internal teams and external customers.
• Design and implement multi-tenant architectures with proper service isolation and security.
• Take end-to-end ownership of backend services from architecture to production support.

Skills

Backend engineering

Distributed systems

API design

Multitenancy

Communication

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Backend / Platform Engineer based in Canada.

As a Backend / Platform Engineer, you will play a key role in designing and developing the core services powering an enterprise AI platform. You will contribute to building scalable backend infrastructure, APIs, orchestration systems, and platform capabilities that support both internal product teams and external customers. Working in a collaborative, remote-first engineering environment, you will take ownership of services throughout their entire lifecycle, from architecture and implementation to deployment and ongoing support. You will tackle complex distributed systems challenges while ensuring reliability, security, and performance. This is an opportunity to shape innovative AI-driven solutions and build robust platform technologies at enterprise scale.

Accountabilities:

• Design, develop, and operate core backend services supporting an enterprise AI platform, including AI gateways, orchestration layers, APIs, and platform infrastructure.
• Build and maintain platform capabilities such as entitlements, tenancy models, usage metering, quotas, and governed data access.
• Develop scalable APIs and intuitive developer experiences for internal engineering teams and external customers.
• Design and implement multi-tenant architectures, ensuring appropriate tenant isolation, service boundaries, and platform-level security controls.
• Build integration frameworks, connector patterns, and reliable data access mechanisms to support diverse enterprise systems.
• Ensure system resilience by addressing distributed systems challenges, including retries, partial failures, consistency, idempotency, and back-pressure.
• Take end-to-end ownership of backend services, covering architecture, development, testing, deployment, monitoring, reliability, and production support.
• Collaborate with cross-functional stakeholders to translate technical and business requirements into effective platform solutions.
• Continuously improve engineering practices, system performance, and operational reliability while balancing delivery speed and technical quality.

Requirements:

• Proven experience developing and operating production backend systems, APIs, or distributed platform services.
• Strong software engineering fundamentals, with the ability to design reliable, scalable, testable, and maintainable applications.
• Experience with platform capabilities such as AI gateways, orchestration systems, entitlements, tenancy, metering, or usage quotas.
• Solid understanding of API design, developer experience, multi-tenant architectures, and service isolation.
• Experience building integration frameworks, connector solutions, event-driven systems, or governed data access patterns.
• Strong knowledge of distributed systems concepts, including retries, consistency, idempotency, back-pressure, and failure management.
• Experience managing services throughout their complete lifecycle, from initial design to production deployment and ongoing maintenance.
• Proficiency in one or more backend programming languages, particularly C#, Python, or Go.
• Familiarity with API gateways, orchestration platforms, event-driven architectures, and platform engineering principles.
• Understanding of AI technologies and architectures, including LLMs, RAG, agentic workflows, tool/function calling, MCP, and A2A.
• Knowledge of event-sourced metering, billing-related services, quotas, and entitlement management is an advantage.
• Experience developing enterprise-scale software used across multiple products, customers, or internal teams.
• Familiarity with AI-assisted development tools, combined with strong code review, testing, and architectural discipline.
• Excellent communication, problem-solving, and collaboration skills, particularly in client-facing and cross-functional environments.
• A pragmatic, adaptable mindset, with the ability to deliver meaningful results while maintaining high engineering standards.

Benefits:

• Permanent, full-time employment opportunity.
• Fully remote working arrangement.
• Opportunity to contribute to an enterprise-scale AI platform and innovative technology solutions.
• Exposure to modern backend technologies, distributed systems, and AI-driven architectures.
• Opportunity to take ownership of critical platform services and influence technical decisions.
• Collaborative environment in involving complex engineering challenges and cross-functional teamwork.
• Professional development opportunities through exposure to emerging technologies and large-scale software engineering practices.