Remote IoT Cloud Architect for AI-Driven Platforms

Raas Infotek LTD; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Raas Infotek LTD seeks a Solution Architect to lead cloud, IoT, and AI-driven platform architecture for remote instrument monitoring. You will define end-to-end architecture across application, transport, and processing layers, establishing scalable, secure governance and integration patterns leveraging AWS.

You will design AI-enabled diagnostics, multi-agent orchestration, and compliant data handling, while ensuring secure device onboarding and resilient connectivity across complex networks.

Responsibilities

• Define and own the end-to-end target architecture and technical roadmap for the next-generation remote instrument monitoring platform.
• Design a scalable, modular, cloud-native architecture comprising Application, Transport, and Processing layers.
• Establish architectural principles, integration patterns, interface contracts, versioning strategies, and ownership boundaries across engineering teams.
• Ensure the platform supports onboarding additional applications and AI agents without significant architectural redesign.
• Evaluate technology choices, build-versus-buy decisions, architectural trade-offs, and modernization strategies.
• Maintain architectural consistency across teams through design reviews, technical guidance, and architecture decision records.
• Own the architecture of the IoT Transport layer, supporting device telemetry, heartbeat monitoring, status updates, events, remote commands, and large-file transfers.
• Design reliable device connectivity solutions that operate across customer firewalls, TLS-inspecting proxies, restricted networks, and intermittent connectivity environments.
• Define secure communication patterns and APIs for instrument-to-cloud and application-to-platform interactions.
• Architect the Model Context Protocol (MCP) layer to expose instrument capabilities and operational functions as governed, permission-controlled, and auditable tools for AI agents.
• Establish scalable cloud infrastructure and integration patterns, preferably leveraging AWS services and cloud-native technologies.
• Define device onboarding, identity management, authentication, authorization, and secure device communication standards.
• Own the Processing layer architecture, including data ingestion, ETL pipelines, operational data stores, analytics platforms, and event-driven processing.
• Design scalable data processing solutions capable of handling large instrument fleets, high-volume telemetry, and variable workloads.
• Define a multi-agent AI architecture comprising an orchestrator and specialized agents that collaborate using Agent-to-Agent (A2A) communication standards.
• Architect LLM-based capabilities for instrument diagnostics, predictive maintenance, anomaly detection, operational intelligence, and service recommendations.
• Establish integration patterns using MCP, A2A, APIs, event streams, and other relevant interoperability frameworks.
• Define AI agent evaluation frameworks, retrieval-augmented generation (RAG), guardrails, prompt management, and model performance monitoring.
• Ensure human approval and authorization mechanisms are incorporated before AI agents execute actions affecting instruments or customer records.
• Define and validate non-functional requirements covering scalability, performance, availability, resilience, security, and disaster recovery.
• Establish architecture standards for telemetry latency, high-volume ingestion, burst handling, multi-GB file transfers, resumable uploads, and data integrity.
• Define observability, monitoring, logging, alerting, and operational support strategies.
• Establish cloud cost optimization principles and cost-per-instrument metrics.
• Define infrastructure automation, environment management, deployment pipelines, and controlled rele

Job description

Raas Infotek LTD seeks a Solution Architect to lead cloud, IoT, and AI-driven platform architecture for remote instrument monitoring. You will define end-to-end architecture across application, transport, and processing layers, establishing scalable, secure governance and integration patterns leveraging AWS.

You will design AI-enabled diagnostics, multi-agent orchestration, and compliant data handling, while ensuring secure device onboarding and resilient connectivity across complex networks.