Solution/Enterprise Architect IRC302023

Description

Our client is developing an advanced industrial asset intelligence platform engineered to drive digital aftermarket transformation and equipment lifecycle monetization. The system integrates edge hardware telemetry, on-premise production software, cloud data warehouses, and generative AI to deliver a unified real-time asset tracking, service optimization, and aftermarket commerce experience for factory operators, field service engineers, and distributors.
The platform architecture centers on a full-stack cloud ecosystem anchored by an Angular 19 frontend, C# 12 .NET 8 microservices, Python FastAPI AI components, Snowflake data warehousing, Azure SQL Managed Instance, Azure OpenAI GPT-4 GenAI diagnostic tools, Azure AI Search, Shopify eCommerce integration, and Azure API Management.
The engineering initiative focuses on defining the overarching end-to-end system architecture, driving the convergence of OT machine telemetry (FitLive) with IT production software (HCSS) and enterprise ERP systems (SAP), architecting high-throughput data pipelines, establishing scalable multi-tenant domain models, and guiding the technical roadmap to deliver high availability and resilient system performance.

Requirements

• 10+ years of experience in enterprise software engineering and cloud solution architecture, with a specialized focus on large-scale industrial or digital platform ecosystems.
• Strong proficiency in multi-tier system design, microservices architecture (.NET 8, C#, Python FastAPI), and modern web frontend frameworks (Angular 19).
• Deep expertise in Microsoft Azure cloud architecture, serverless compute, container orchestration, and Infrastructure as Code (Terraform, AzureRM).
• Proven experience in enterprise data architecture, designing hybrid data models across relational databases (Azure SQL MI), data warehouses (Snowflake), object storage (Azure Blob), and cache layers (Redis).
• Expert-level knowledge of system integration patterns, RESTful APIs, messaging brokers (Azure Service Bus), API gateways (Azure API Management), and third-party platform integrations (Shopify, SAP).
• Solid background in AI system architecture, including RAG-based Generative AI workflows (Azure OpenAI GPT-4), semantic search engines (Azure AI Search), and Knowledge Graph implementations.
• Practical experience in cloud security architecture, identity federation (Azure Entra External ID), zero-trust models, and regulatory compliance governance.
• Solid understanding of IT/OT hardware convergence, real-time telemetry ingestion pipelines, predictive maintenance models, and edge-to-cloud data bridging.
• Self-organized personality with outstanding executive communication, technical leadership, and decision-making skills across cross-functional engineering teams and technical stakeholders.

Job responsibilities

• Define the global end-to-end solution architecture for the platform, ensuring seamless alignment between business strategy, functional capabilities, and technical execution.
• Architect complex system integrations across disparate data sources, bridging OT edge telemetry (FitLive), factory-floor IT systems (HCSS), cloud services, and enterprise ERP systems.
• Design high-throughput, low-latency data ingestion pipelines and unified canonical data models across Snowflake, Azure SQL MI, and asynchronous event streams.
• Formulate technical strategies for Generative AI integration, Knowledge Graph structures, Document Intelligence manual parsing, and predictive analytics microservices.
• Establish architectural governance, non-functional requirements (NFRs), security frameworks, multi-tenant isolation rules, and disaster recovery strategies across active cloud environments.
• Evaluate emerging technologies, conduct technical feasibility assessments, build proof-of-concept (PoC) architectures, and guide technical build-versus-buy decisions.
• Enforce cloud engineering best practices, reviewing microservice contracts, database schemas, API management policies, and IaC deployment patterns.
• Deliver technical leadership to domain architects, engineering leads, and DevOps teams, while serving as the primary technical advisor to product management and client stakeholders.