<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>About Bristlecone</strong></p><p>Bristlecone is a leading supply chain and business analytics advisor, serving global hubs across multiple industries. Rated by <strong>Gartner</strong> among the top ten system integrators in the supply chain space, we are uniquely positioned to solve contemporary business problems.</p><p><br/></p><p>We are a trusted partner to global icons including <strong>Applied Materials, Exxon Mobil, Unilever, and Nestle</strong>. Join us to build the high-performance systems that keep the world moving.</p><p><br/></p><p><strong>Role Summary</strong></p><p><br/></p><p>This is a remote-first position with a significant international travel requirement. You should expect to travel between 50–60% of the time to support our global operations in countries including France, China, Germany, India, Morocco, the UK, Tunisia, and the USA, depending on project needs.</p><p><br/></p><p>We are seeking an experienced Solution Architect to lead the end-to-end architecture and successful rollout of enterprise-grade Digital Twin solutions. You will be responsible for designing scalable, high-performance digital twin architectures that integrate physical assets, real-time data streams, simulation models, analytics, and enterprise systems to deliver measurable business outcomes such as predictive maintenance, operational optimization, and reduced downtime.</p><p>This is a senior technical role that combines deep architecture expertise with strong leadership in large-scale digital twin implementations (including platforms like ScaleTwin, ScaleOut Digital Twins, Azure Digital Twins, Siemens, or custom solutions).</p><p><br/></p><p><strong>Key Responsibilities</strong></p><ul><li>Lead the solution architecture for Digital Twin rollouts, including high-level and detailed design of twin models, data architecture, integration patterns, and deployment strategy.</li><li>Define end-to-end architecture covering:</li><li>Digital Twin model hierarchy and entity relationships</li><li>Real-time data ingestion and synchronization from IoT, SCADA, historians, and edge devices</li><li>State management, event processing, and simulation engines</li><li>Integration with enterprise systems (ERP, MES, PLM, EAM)</li><li>Analytics, and visualization layers</li><li>Select and design the optimal technology stack for scalable digital twin deployments, including in-memory computing platforms (e.g., ScaleTwin/ScaleOut), cloud services (AWS, Azure), streaming platforms (Kafka, MQTT), and containerization (Kubernetes).</li><li>Create architecture blueprints, diagrams, and documentation (including logical, physical, and deployment views) to guide implementation teams.</li><li>Conduct architecture reviews, risk assessments, and performance/scalability evaluations for large-scale twin deployments handling millions of entities and high-velocity data.</li><li>Collaborate with Configuration Leads, Consultants, Data Engineers, and Client Stakeholders to ensure the solution is configurable, maintainable, and aligned with business requirements.</li><li>Define standards, best practices, and reusable reference architectures for future Digital Twin rollouts.</li><li>Provide technical leadership during pilot phases, full-scale rollout, go-live, and hyper-care periods.</li><li>Mentor configuration teams on digital twin architecture principles.</li></ul><p><br/></p><p><strong>Required Qualifications &amp; Experience</strong></p><p><br/></p><ul><li>10+ years of overall IT/solution architecture experience, with at least 4–6 years in Digital Twin, IIoT, IoT platforms, or real-time simulation solutions.</li><li>Proven track record in successfully architecting and rolling out large-scale Digital Twin solutions for manufacturing, logistics, energy, or asset-intensive industries.</li><li>Strong expertise in:</li><li>Digital Twin platforms and frameworks (ScaleTwin, ScaleOut Digital Twins, Azure Digital Twins, NVIDIA Omniverse, or equivalent)</li><li>Real-time data architectures (Kafka, MQTT, OPC UA, Spark Streaming)</li><li>Cloud platforms (AWS IoT, Azure IoT Hub, Google Cloud)</li><li>In-memory computing, complex event processing, and stateful applications</li><li>Microservices, containerization (Docker, Kubernetes), and DevOps practices</li><li>Bachelor’s or Master’s degree in Computer Science, Electrical/Mechanical/Industrial Engineering, or related field.</li></ul><p></p> </div>