Design, build, operate, and support backend services powering an enterprise AI platform. Responsibilities include developing APIs, gateways, orchestration, tenancy, entitlements, integrations, data access patterns, and platform services. The engineer owns services across architecture, implementation, testing, deployment, monitoring, reliability, and support while addressing distributed-system concerns such as failure handling, consistency, idempotency, retries, and back-pressure.
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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