Designs, builds, deploys, operates, and supports backend services powering an enterprise AI platform. Responsibilities include developing APIs, orchestration, entitlements, tenancy, data access, integration frameworks, connectors, metering, and platform services. The role requires expertise in distributed systems, reliability, failure handling, multi-tenant architecture, testing, monitoring, and service ownership, along with strong communication and collaboration in a client-facing consulting environment.
Backend / Platform Engineer
Inviso is partnering with one of our clients to find an experienced Backend / Platform Engineer to join their team working remotely. Inviso is managing the recruitment and placement process for this opportunity. This is a remote, direct-hire permanent employee position for our client that is a global multi-billion dollar software conglomerate.
The Backend / Platform Engineer is responsible for designing, building, and operating the core services that power an enterprise AI platform. This role contributes to the AI gateway, orchestration layer, entitlements, tenancy model, data access patterns, integration frameworks, APIs, and platform services that product teams and customers depend on.
The Engineer owns services end to end, from design and implementation through testing, deployment, reliability, and support. The ideal candidate is a strong backend engineer who understands distributed systems, failure modes, clean boundaries, platform APIs, and pragmatic trade-offs.
Experience & Skills Required
- Experience building and operating production backend, API, or distributed platform services.
- Strong software engineering skills with experience designing reliable, testable, and maintainable services.
- Experience with AI gateway, orchestration, entitlements, tenancy, metering, quotas, or similar platform capabilities.
- Ability to design APIs and developer experiences for internal and external consumers.
- Experience with multi-tenant systems, tenant isolation, service boundaries, and platform-level enforcement patterns.
- Experience building integration frameworks, connector patterns, governed data access, or reliable data on-ramps.
- Strong understanding of retries, partial failure, consistency, idempotency, back-pressure, and operational failure modes.
- Experience owning services through design, development, testing, deployment, monitoring, and support.
- Strong communication and collaboration skills for client-facing consulting environments.
- Pragmatic mindset with the ability to ship meaningful value quickly while maintaining engineering quality.
Desired Qualifications
- Experience with C#, Python, Go, or similar backend languages.
- Experience with API gateways, orchestration systems, connector frameworks, event-driven systems, or platform engineering.
- Experience with AI, LLM, RAG, agentic workflows, tool/function calling, MCP, A2A, or AI development lifecycle practices.
- Experience with event-sourced metering, quotas, entitlements, or billing-related platform services.
- Experience building enterprise-scale software used by multiple products, customers, or internal teams.
- Experience using AI-assisted development tools while maintaining strong review, testing, and architecture discipline.
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
