Tech Stack
AWSAzureCloudGoGoogle Cloud PlatformGraphQLIoTJavaScriptKubernetesMicroservicesNode.jsPython
About the role
- Design and deploy scalable architectures for manufacturing use cases including industrial operations that include SCADA/HMI, EDA, IoT, Machine Learning, AI, and advanced analytics.
- Lead technical workshops, prototype solutions, and oversee platform deployment and optimization.
- Collaborate with product and engineering teams to incorporate customer feedback into the product roadmap.
- Advise customers on Articul8 product adoption strategies with a focus on differentiating capability, security, cost, and operational efficiency.
- Architect and tune Kubernetes-based and containerized infrastructure leveraging cloud platforms (AWS, Azure, GCP, or on-premises) to ensure infrastructure excellence.
- Develop reusable solution templates and document best practices.
- Partner with sales and business development to drive cloud adoption and align solutions with industry trends.
- Continuously monitor and improve deployed solutions for performance and scalability.
- Communicate technical concepts clearly to diverse audiences and advocate for customer needs internally.
- Stay current with emerging manufacturing and cloud technologies to inform strategy and ability to support other industry verticals when required.
- Guide product roadmap by driving feedback and market insights into solution strategy and product development in complex enterprise environments.
- Serve as a senior technical partner merging manufacturing domain expertise, cloud architecture proficiency, and customer success engagement.
Requirements
- 10+ years of experience in solution architecture, technical implementation, or enterprise software delivery, including significant engagement with executive and technical leadership.
- Strong expertise in cloud platforms, Kubernetes orchestration, containerization, microservices architecture, and modern programming languages (e.g., Python, Node.js, Go).
- Deep understanding of manufacturing industry specific challenges, IT/OT convergence, and digital transformation.
- Experience with enterprise integration patterns, RESTful APIs, GraphQL, and data engineering.
- Proven ability to build effective prototypes, demos, and production-grade deployments.
- Exceptional communication skills, capable of articulating complex technical concepts clearly across business and engineering audiences.
- Expertise in generative AI building blocks and at least one specialization in AI/ML pipelines, API design, data engineering, vector/graph databases, or AI model orchestration.
- Willingness and ability to travel for customer workshops, deployments, and support as necessary.