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The Senior Product Designer will lead user-centered design for enterprise applications, conducting user research, creating prototypes, collaborating with cross-functional teams, and influencing design practices across the organization.

Lead design and delivery of cloud-native Data Integration Services: define scalable data access patterns, storage integrations, dataset lifecycle and permissioning, ensure observability and governance, and mentor engineers to drive platform adoption.

Design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data. Implement data storage and ingestion for ML workloads, enable BI and visualization tools, own features end-to-end, maintain CI/CD and observability, and collaborate with data scientists to ensure secure, reliable, performant systems.

Lead design and delivery of cloud-native Data Integration Services to enable discovery, access, sharing, and governance of large simulation and ML datasets. Define data access patterns, storage integrations, permissioning, lifecycle, observability, and platform standards while mentoring engineers and driving cross-team adoption.

Work with customers and cross-functional teams to turn AI-driven simulation research into reusable engineering applications. Build and maintain frontend interfaces and backend services, design APIs, write clean, tested code, optimise performance, and contribute to architecture and CI/CD. Translate customer workflows into product capabilities and mentor junior engineers.

The Senior Machine Learning Engineer will lead the deployment of ML models, design scalable systems, mentor team members, and collaborate with customers to solve engineering challenges.

As the Lead Forward Deployed Software Engineer, you will oversee multiple projects ensuring successful software delivery while cultivating talent and enhancing customer workflows across engineering disciplines.

As a Forward Deployed Software Engineer, you will build and deploy applications using physics AI models to solve complex engineering problems, collaborating with cross-functional teams and directly engaging customers for feedback.

Develop and deploy AI agents for engineering workflows, collaborating with domain experts, and improving the platform's functionality through systematic evaluations.

As a Principal AI Engineer, you'll architect the Agentic stack for AI-driven simulation software, focusing on agent observability, deployment, sandboxing, evaluations, and governance within engineering workflows.