• Own Messaging & Positioning • Develop and refine SubQ’s core messaging, positioning, narrative, and category strategy across products, research initiatives, and GTM efforts. • Translate Complex Technical Concepts • Work closely with researchers and engineers to deeply understand complex AI infrastructure concepts and turn them into clear, credible, and differentiated messaging for technical audiences. • Drive Product Launches • Lead messaging and GTM support for product launches, benchmark releases, research announcements, demos, and technical campaigns. • Shape the Company Narrative • Help define how SubQ communicates its long-term vision, technical differentiation, and market positioning within the broader AI ecosystem. • Partner Across Teams • Collaborate cross-functionally with engineering, research, leadership, recruiting, GTM, and content teams to ensure consistency and clarity across all external communication. • Support Founder-Led Content • Partner with leadership on high-impact thought leadership, technical commentary, social content, conference materials, and strategic communications. • Understand the Market • Track trends across AI/ML, LLMs, inference, agents, long-context systems, developer tooling, open-source ecosystems, and frontier AI research to inform positioning and messaging strategy. • Develop Technical GTM Strategy • Help shape developer-facing and technical GTM initiatives including launch strategy, content strategy, competitive positioning, and ecosystem engagement.

Role Description DDN is seeking a Client Director – Strategic AI Infrastructure to drive revenue growth in the U.S. West Coast region within our Artificial Intelligence business unit. This is a quota-carrying role responsible for developing strategic enterprise opportunities and expanding DDN’s presence within organizations building large-scale AI and high-performance computing environments. In this role, the Account Executive will operate as a Strategic AI Client Director, partnering with enterprise customers, research institutions, and cloud organizations to deliver high-performance data infrastructure solutions that support advanced AI workloads. The successful candidate will work closely with internal engineering teams, solutions architects, and channel partners to design and deliver complex AI infrastructure solutions supporting GPU computing, large-scale model training, and data-intensive workloads. Key Responsibilities - Act as a Strategic AI Client Director within the assigned West Coast territory, driving adoption of DDN’s AI infrastructure solutions across enterprise and research organizations. - Drive revenue growth and achieve or exceed assigned sales quota across the West Coast region. - Develop and execute strategic territory and account plans targeting organizations building large-scale AI and high-performance computing environments. - Identify and qualify new opportunities across industries including financial services, healthcare, telecommunications, technology, research institutions, and large enterprise organizations. - Build trusted relationships with senior technical leaders, AI infrastructure teams, and executive decision-makers within target accounts. - Partner with solutions architects and engineering teams to design and present AI infrastructure and high-performance data storage solutions. - Deliver compelling presentations, product demonstrations, and proposals showcasing the value of DDN’s AI-optimized storage platforms. - Manage the full enterprise sales cycle including pipeline development, forecasting, contract negotiation, and deal closure. - Develop strong relationships with channel partners, system integrators, OEM partners, and distributors to expand market reach. - Stay current on market trends related to AI infrastructure, GPU computing, large-scale model training, and high-performance data environments. - Represent DDN at industry events, conferences, and customer engagements to generate new opportunities and strengthen market presence. Qualifications - 8+ years of experience in enterprise technology sales, preferably within storage, compute, networking, or infrastructure platforms. - Demonstrated experience selling AI infrastructure, HPC solutions, cloud platforms, or enterprise data center technologies. - Experience managing complex enterprise sales cycles involving technical buyers and executive stakeholders. Preferred Experience - Experience selling AI infrastructure, GPU clusters, or high-performance computing platforms. - Familiarity with the AI ecosystem including technologies from NVIDIA, Intel, AMD, Cerebras, Graphcore, or Google TPU. - Knowledge of enterprise storage technologies including SAN, NAS, object storage, and parallel file systems. - Experience working with channel partners, system integrators, and distributor ecosystems. - Familiarity with technologies such as Kubernetes, OpenStack, and large-scale AI data center environments. Benefits - Work at the forefront of AI infrastructure innovation, helping organizations solve demanding data challenges. - Collaborate across engineering, sales, and customer success to deliver cutting-edge technology. Company Description DataDirect Networks, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

• Develop and deploy ML models and LLM-based solutions for product outcome prediction • Build workflows where users input product details and receive predictive insights • Enhance an existing AI agent into a decision-making/prediction system • Work with product and assortment data for feature engineering and modeling • Integrate LLM capabilities to improve reasoning and contextual understanding • Continuously evaluate and improve model performance

• Research, design, develop, and deploy innovative AI/ML and Generative AI solutions across various mission-focused problem sets • Support development of advanced AI capabilities using technologies such as large language models and cloud-native AI services including AWS Bedrock • Participate in all phases of the software engineering lifecycle, including research, requirements analysis, solution design, model development, integration, deployment, evaluation, and testing