Solutions Architect

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.