Senior Product Designer, Client-Facing
Lead customer delivery engagements and translate client needs into actionable design solutions.
Remote • United States
- Full Time
- $170,000 – $210,000
- Min. 5 YOE
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Lead customer delivery engagements and translate client needs into actionable design solutions.
Architect the Agentic stack for production-grade AI workflows across engineering platforms and secure, observable agent execution.
Own core multi-cloud infrastructure design, Kubernetes ops, and reliability for AI workloads.
Architect security tooling in CI/CD, leads threat modeling, and drives secure development lifecycle improvements.
Bridge customer needs with AI-enabled engineering solutions to drive multi-industry adoption and roadmap alignment.
Senior Platform Engineer focused on observability, FinOps and multi-cloud IAM to improve platform reliability and developer experience.
Senior Software Engineer to design and build enterprise-grade authentication, RBAC/ABAC, telemetry, and multi-tenant access control for a secure AI-native platform.
Leads cross-functional engineering on scalable front-end and backend services powering AI-driven engineering applications.
Senior FEA Engineer delivering high-fidelity simulations and multi-physics models for customers across aerospace, materials, energy, and automotive.
Leads data-driven modelling and deep learning initiatives to predict and control physical systems.
Build and scale the Agentic stack within a production-grade platform enabling AI workflows for engineering, with secure runtimes and observability.
Deliver high-fidelity multi-physics CFD simulations and CAE solutions for customers, integrating AI tools and data-driven design optimization.
Leads forward-deployed projects by translating customer engineering problems into reusable product capabilities.
Lead deployment of ML models and engineering surrogates to customer production environments, guiding architecture and measurable delivery.
Lead deployment of ML models and engineering surrogates to customer production environments with scalable pipelines and cloud/on-prem solutions.
Senior ML engineer leading deployment of ML models and surrogates across customer production environments with measurable outcomes.
Develop ML models and scalable solutions for physics-based problems, transforming prototypes into robust, distributed training implementations across multi-node GPU/cloud environments.
Translate physics and engineering challenges into mathematical formulations; build models using ML for physical systems.
Owns frontend and backend engineering tasks across customer-facing work, delivering reusable product capabilities from real engineering insights.
Lead data science work streams, architect deep learning models, and deploy production-ready data pipelines.
Design and operate distributed ML training and serving infrastructure for neural operators at scale.
Apply finite element analysis to real-world challenges across multiple industries, building CAE models integrated with AI-tools.
Design and build data platforms and distributed services for AI-driven multi-physics simulations across ML lifecycle.
Build and deploy applications that utilize physics AI models to enable customers to build better, faster, and cheaper.