Enterprise Solution Architect leading WMS implementation projects at Blue Yonder. Driving value through defining business processes and providing technical architectural solutions.
About the role
- Solution Architect developing comprehensive AI infrastructure solutions for deployment at d-Matrix. Collaborating with clients to enable successful integration of d-Matrix based solutions.
Responsibilities
- Develop end-to-end AI infrastructure reference solutions optimized for d-Matrix servers including compute, networking, storage, and orchestration layers, in collaboration with various internal teams.
- Create reference blueprints that integrate smoothly into cloud-native and on-prem environments.
- Develop infrastructure-as-code templates and examples using Ansible, Terraform, and Helm for provisioning d-Matrix-based nodes and clusters.
- Integrate with Kubernetes-based systems to enable model deployment, auto-scaling, and fault-tolerant execution.
- Design and deploy telemetry and monitoring frameworks to support real-time visibility into d-Matrix cluster health, job status, and system performance.
- Integrate with industry-standard observability stacks (e.g., Prometheus, Grafana, OpenTelemetry) for data collection, visualization, and alerting.
- Develop dashboards, health check systems, and metric pipelines that track performance, availability, and operational KPIs
- Collaborate with performance and software teams to validate infrastructure using real-world workloads and benchmarks.
- Incorporate telemetry hooks for benchmark reporting and feedback-driven tuning.
- Create and publish detailed infrastructure deployment guides, monitoring configuration templates, and operational best practices.
- Collaborate with customers and OEM/ISV ecosystem, enable them to adopt and customize reference solutions to their specific datacenter environments and/or software stacks.
Requirements
- Bachelor's or Master’s degree in Computer Science, or related technical field
- 10+ years of experience in infrastructure solution architecture, systems management, DevOps, or platform engineering roles.
- Experience working with GPUs, custom AI accelerators or heterogeneous compute environments.
- Proven expertise in building, managing, and monitoring full-stack AI infrastructure at scale.
- Strong scripting/automation skills: Python, Bash, Ansible, Terraform, Helm, Docker/Kubernetes.
- Deep understanding of orchestration technologies (Kubernetes, Ray, KServe, etc.), containerization, server clusters, multi-tenant serving, etc.
- Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.)
- Strong skills in scripting and automation (e.g., Python, Bash, Ansible, Terraform, Helm).
- Familiarity with model serving and orchestration platforms (e.g., Triton Inference Server, Ray Serve, Kubeflow).
- Strong system debugging and incident response skills.
- Outstanding collaboration and communication skills.
Benefits
- Offers Equity
- Offers Bonus
- Medical/Dental/Vision/401k
- Comprehensive benefits centered around employee wellbeing
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