Software Architect - Cloud & Edge AI Platforms

ABOUT WIND RIVER

Wind River is a global leader in delivering software for mission-critical intelligent systems. For more than four decades, the company has been an innovator and pioneer, powering billions of systems that require the highest levels of security, safety, and reliability. The company has received industry recognition for its technology innovation and leadership, and for its workplace culture, including global Great Place to Work certification and being named a "Top Workplace" for ten consecutive years.

Wind River helps customers across automotive, aerospace, defense, industrial, medical, and telecommunications industries solve complex technology challenges on their journey toward the new intelligent machine economy. The company's software powers generation after generation of the safest, most secure systems in the world. Examples include playing a key role in NASA space missions such as Artemis I, the James Webb Space Telescope, and multiple Mars rovers. We've achieved recent 5G milestones including the world's first successful 5G data session with Verizon and building one of the largest Open RAN networks in the world with Vodafone.

About the Role

We are looking for a Software Architect to define and drive the architecture of next-generation platforms that seamlessly integrate cloud-native technologies with high-performance edge AI. This role sits at the intersection of distributed systems, AI/ML infrastructure, and mission-critical edge computing.

What You'll Do

Platform and Architecture Leadership

• Architect end-to-end cloud-to-edge AI platforms that support model training, optimization, deployment, and lifecycle management.
• Define scalable, modular, and secure architectures for distributed AI workloads across heterogeneous edge environments.
• Lead the design of cloud-native services, APIs, and orchestration layers that integrate with Wind River Studio and edge operating systems.
• Establish architectural patterns for hybrid and multi-cloud deployments, including Kubernetes-based edge clusters.

• Design systems that support model versioning, CI/CD for AI, inference pipelines, and real-time data processing.
• Integrate AI frameworks (TensorFlow, PyTorch, ONNX Runtime, TensorRT, etc.) into cloud-edge workflows.
• Collaborate with hardware teams to leverage acceleration technologies (GPU, NPU, FPGA, VPU) for optimized inference at the edge.

• Ensure platform architectures meet stringent requirements for determinism, safety, and reliability across mission-critical industries.
• Define security models for distributed AI, including data integrity, model protection, and secure edge-to-cloud communication.
• Optimize performance, scalability, and resource utilization across diverse edge hardware profiles.

• Partner with product management to define platform strategy, roadmap, and customer-driven requirements.
• Work with engineering teams to translate architectural vision into robust, production-ready implementations.
• Engage with customers, partners, and industry groups to represent Wind River's technical leadership in cloud and edge AI.

• 10+ years of experience in software architecture, distributed systems, cloud platforms, or embedded systems.
• Strong expertise in cloud-native technologies (Kubernetes, containers, microservices, service mesh).
• Deep understanding of AI/ML infrastructure, model deployment, and edge inference optimization.
• Experience with real-time systems, embedded Linux, or RTOS-based environments.
• Proficiency in C/C++, Python, and modern DevOps practices.
• Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid cloud architectures.

• Experience with mission-critical or safety-critical systems (automotive, aerospace, industrial, medical).
• Knowledge of virtualization technologies (KVM, ACRN, hypervisors) and secure partitioning.
• Background in distributed AI, federated learning, or edge-to-cloud orchestration frameworks.
• Contributions to open-source cloud, AI, or embedded systems projects.

• A systems-level mindset and the ability to design architectures that bridge cloud and edge environments.
• A passion for building intelligent, resilient platforms that power the next generation of autonomous and connected systems.
• Strong communication skills and the ability to influence technical direction across teams.
• Curiosity, innovation, and a drive to push the boundaries of cloud-edge AI integration.