• Responsible for supporting the hardware and software aspects of Brain Corp’s fleet of robots • Proactively monitor deployed fleet of robots remotely using internal tools to identify and solve issues effectively • Conduct independent technical troubleshooting on customer-reported issues and implement effective resolutions • Develop and expand comprehensive expertise in Brain Corp’s robotic systems, encompassing hardware, software, navigation kits, sub-system and cloud infrastructure. Utilize this knowledge to effectively troubleshoot and resolve issues as they arise • Act as a Subject Matter Expert (SME) for both direct customers and Original Equipment Manufacturers (OEMs), adept at understanding their needs and resolving any issues they encounter in a timely and efficient manner • Lead customer meetings and discussions • Act as the primary liaison between our company and our end users • Lead internal or external customer related initiatives addressing issues as they arise • Collaborate closely with the Account Management team to address and resolve any issues or concerns raised by end users • Proactively identify opportunities to enhance customer satisfaction and retention • Coordinate meetings with service providers and OEMs: • Organize and lead regular meetings with service providers (SPs) and OEMs to discuss current issues, implement changes, and address any complaints • Ensure effective communication and collaboration between all parties to maintain strong working relationships and resolve issues promptly • Document meeting outcomes, track action items, and follow up to ensure timely resolution of all concerns • Provide issue resolution and continuous improvement: • Take ownership of the resolution process for any issues reported by end users, SPs, or OEMs • Work cross-functionally with internal teams to identify root causes and implement corrective actions • Continuously seek ways to improve processes and enhance the overall customer experience • Lead the quality resolution process, initiating from customer-reported symptoms, progressing through troubleshooting cycles to identify root causes effectively • Provide training & enablement to OEM/customer when needed; providing on-site support within geographic region as needed • Serve as an escalation point between Tech Support and Fleet Ops and Engineering teams • Assist with the creation and monitoring of team metrics • Provide training and support to junior staff and mentor team members • Travel up to 20% to Brain Corp offices, OEM partner locations, and customer sites as needed.

• Engage with local support teams during pre-installation phase as a consultant to design the integration of the solution with the local infrastructure and answer all IT related questions. • Ensure systems are setup for remote diagnostics and health monitoring • Engage with the development and operations organization to provide recommendations to manuals, training and customer facing material. • Perform automated deployments through the use of configuration management technology; • Provide support to the installations within the SLA as agreed using our processes. • Conduct detailed troubleshooting and analysis of system or SW and infrastructure problems that affect reliability, performance, etc. of our delivered systems. • Support factory and development teams with first deployments, installs and upgrades of newly introduced systems and modules to ensure accurate working order.

Role Description Our customers rely on our platform to orchestrate complex warehouse, transportation, and last-mile logistics operations. As Product Delivery Lead, you will bridge customer operations and R&D, ensuring we build solutions that solve real business problems and deliver measurable outcomes. This is an API-first product leadership role operating within our Product Operating Model. You will partner closely with customers, Engineering, and Product to translate operational challenges into product outcomes, guide delivery, and continuously validate value through customer feedback, data, and AI-enabled product practices. Outcomes — What Success Looks Like - Deliver Customer-Centric Solutions - Translate customer needs into clear product outcomes that guide R&D. - Deliver scalable API capabilities that improve warehouse, transportation, and last-mile operations. - Accelerate Product Delivery - Apply Product Operating Model practices to rapidly validate ideas through Build-Test-Learn cycles. - Reduce time from concept to customer value using customer feedback, prototypes, and data. - Improve Customer Operations - Drive enhancements to sorting, routing, sequencing, loading, and execution capabilities that improve customer KPIs such as throughput, dwell time, and delivery performance. - Ensure APIs provide reliable, real-time operational data. - Deliver Successful Integrations - Partner with customers and Engineering to define API contracts and support integrations across WMS, TMS, ERP, and mobile platforms. - Remove technical barriers that impact adoption and customer success. - Leverage AI to Improve Product Delivery - Use AI to enhance product discovery, research, documentation, backlog refinement, and analysis. - Transform customer feedback and usage data into actionable product insights while applying sound judgment to AI-generated recommendations. - Build Strong Partnerships - Foster trusted relationships across Product, Engineering, Customer Success, and customers. - Promote transparency, collaboration, and continuous improvement. Skills & Competencies — How the Work Gets Done - Product & Technical Expertise - Strong understanding of REST APIs, authentication, web services, payloads, webhooks, and API documentation. - Comfortable discussing integrations, API contracts, and data flows with Engineering. - Experience with enterprise integrations involving WMS, TMS, ERP, or similar platforms. - Familiarity with SaaS products, mobile applications, and product analytics (SQL or BI tools). - Logistics & Product Leadership - Strong understanding of warehouse, transportation, and last-mile operations. - Experience working within a Product Operating Model, using outcome-based planning, experimentation, and continuous discovery. - Ability to balance customer needs, technical feasibility, and business priorities. - Excellent stakeholder management and facilitation skills. - Professional fluency in French and English. - AI-Enabled Ways of Working - Uses AI responsibly to improve product management practices, research, prioritization, and analysis. - Applies critical thinking to validate AI outputs and keep recommendations grounded in customer value. Benefits - Shape the future of an API-first logistics platform used by organizations managing complex supply chain operations. - Collaborate closely with Product leadership, Engineering, Customer Success, and customers. - Define AI-enabled ways of working that improve how products are discovered, built, and delivered. - Work in a culture that prioritizes work-life balance and fosters an environment for individual accomplishments. - Competitive compensation, great benefits, remote and flexible work hours. Location & Salary Range This is a remote position, and the salary range for this role is $85,000–$95,000 CAD. Compensation information provided is a good faith estimate for this position only. Factors that may be used to determine your actual salary may include your specific skills as well as the years of experience you have.

Role Description DDN is expanding our Enterprise and Sovereign AI Solution offerings, for example Hyperpod - a turnkey NVIDIA AI Data Platform built on DDN Infinia storage, NVIDIA AI Enterprise (NVAIE), and Supermicro reference hardware, optimized for inference and RAG workloads. Our support organization is deep on storage (Infinia, EXAScaler); we are now hiring an AI platform specialist to lead supportability and enablement for the AI side of the stack. - Act as the primary NVIDIA AI Enterprise and vector database solutions expert for HyperPOD customer environments. - Own complex end-to-end triage across GPU, NVAIE services, vector DB, Kubernetes, Docker, high-speed networking, and Infinia storage. - Diagnose and resolve performance bottlenecks in RAG and agentic AI workflows. - Collect and interpret logs and telemetry across Linux, containers, Kubernetes, GPU stack, vector DB, and storage/networking. - Author and maintain support triage runbooks and checklists for HyperPOD. - Define and validate unified diagnostics bundles that capture the right logs/configs/metrics. - Collaborate with observability and tools teams to shape dashboards that surface platform health and RAG/service-level metrics. - Build hands-on labs and PoCs that mirror customer RAG and agentic AI use cases on HyperPOD. - Develop reusable technical assets to accelerate time-to-value for customers, PS, and Support. - Provide structured feedback from early field cases and PoCs into Product Management and Engineering. - Collaborate closely with NVIDIA solutions architects, OEM architects, PS, and Support Innovation. Qualifications - 5+ years in Linux-based infrastructure roles (SRE, MLOps, platform engineering, or L2/L3 support) supporting production systems; 8+ years total technical experience preferred. - Strong hands-on experience with containers and Kubernetes. - Demonstrated experience operating GPU-accelerated workloads in production. - Practical experience with AI storage and networking for HPC/AI clusters. - Experience with one or more vector databases (Milvus, Qdrant, Pinecone, etc.). - Solid understanding of RAG and Generative AI workflows. - Familiarity with NVIDIA AI Enterprise components and toolchain. - Experience designing, operating, or supporting MLOps / GenAI pipelines. - Strong diagnostic skills across Linux, containers, Kubernetes, GPUs, storage, and networking. - Track record of building reusable technical assets that improve support readiness. - Excellent communication skills. Requirements - Prior experience with scale-out storage in GPU/AI environments. - Direct experience crafting and operating RDMA-accelerated HPC/AI clusters at scale. - Hands-on work with NVIDIA reference blueprints or similar enterprise AI architectures. - Familiarity with AI observability and responsible AI practices. - Experience with observability stacks tuned for AI workloads. Benefits - Competitive salary and performance-based bonuses. - Comprehensive health, dental, and vision insurance. - Retirement savings plan with company match. - Flexible working hours and remote work options. - Professional development opportunities. Company Description DDN is a leading provider of AI data solutions, focused on delivering high-performance storage and networking solutions for enterprise and sovereign AI applications.