Senior Solutions Architect, Physical AI Cloud

• Help partners build scalable, observable, GPU-accelerated Physical AI pipelines through agentic workflows, cloud-native technologies, and NVIDIA frameworks such as OSMO.
• Support development of Physical AI data factories for data ingestion, preprocessing, annotation, filtering, synthetic data generation, training, simulation, and evaluation.
• Develop a deep understanding of robotics workload scaling and translate customer requirements into optimized cloud-native architectures.
• Improve scheduling, cost, storage access, networking, and GPU utilization across hybrid infrastructure.
• Accelerate distributed inference using NVIDIA technologies such as NIM, Tensor RT-LLM, v LLM, and SGLang.
• Collaborate with business, engineering, and product teams.
• Provide technical guidance and mentorship to customers implementing Physical AI at scale.

Requirements

• BS in Computer Science, Computer Engineering, or a related field, or equivalent experience.
• 5+ years of experience in Solution Architecture or Infrastructure Engineering.
• Experience advancing AI/ML systems from proof of concept to production on private/public cloud environments.
• Experience scaling Robotics workloads in multimodal model training, inference, robot learning and simulation, or large-scale data processing and generation.
• Strong hands-on experience designing, deploying, and operating Kubernetes-based platforms for distributed GPU and AI workloads.
• Expertise in networking, including DNS, load balancing, TCP/IP, and firewalls.
• Expertise in storage technology.
• Expertise with workflow orchestration software such as Airflow and Argo.
• Expertise in modern Dev Ops practices including Git Ops, Ia C, and observability.
• Experience orchestrating efficient GPU workloads.
• Excellent communication skills to convey technical concepts to diverse audiences.
• Preferred: hands-on experience with robotics frameworks such as ROS2 and NVIDIA platforms such as Isaac Lab, Isaac Sim, GR00T, or Cosmos.
• Preferred: exposure to large-scale Robotics data curation, annotation, and filtering pipelines, including AI models for data labeling.
• Preferred: experience deploying NVIDIA inference technologies such as Dynamo, NIM, Triton, and v LLM using quantization.
• Preferred: proficiency using and developing agentic workflows.
• Preferred: broad technical expertise across networking, compute, and storage systems such as S3, NFS, and Lustre, with hands-on experience building and debugging REST and g RPC APIs.
• Core Competencies

Demonstrates expertise in designing and deploying scalable, GPU-accelerated Physical AI pipelines using NVIDIA frameworks and cloud-native technologies.

Proficient in orchestrating AI/ML systems and robotics workloads while providing technical guidance and mentorship.

• Highest-signal resume keywords
• Solution Architecture
• Kubernetes-Based Platforms
• AI/ML Systems Deployment
• Networking Expertise
• Workflow Orchestration Software
• ATS Optimization Keywords
• Hard Skills
• GPU Utilization
• Robotics Workload Scaling
• Cloud-Native Architectures
• Distributed Inference
• Data Processing
• AI Model Training
• Dev Ops Practices
• REST APIs
• GRPC APIs
• Synthetic Data Generation
• Soft Skills
• Excellent Communication Skills
• Industry Keywords
• Physical AI
• Robotics Frameworks
• Data Curation
• Annotation Pipelines
• Hybrid Infrastructure
• Tools & Technologies
• NVIDIA OSMO
• Airflow
• Argo
• NIM
• Tensor RT-LLM
• VLLM
• Isaac Lab
• Isaac Sim
• Dynamo
• Triton
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