Product Marketing Manager – DSW UnifyAI OS | Enterprise AI Operating System

About the Role At DSW, we are building the Enterprise AI Operating System that enables organizations to operate AI as governed, scalable infrastructure. We are looking for a Product Marketing Manager who can translate deep technology into clear market narratives, define category positioning, and drive go-to-market strategy as we expand globally, with a strong focus on the US market. This is not a traditional PMM role. This role sits at the center of product, market, and category creation. What You Will Own1. Positioning & Category Narrative Define and evolve the positioning of DSW UnifyAI OS Build messaging frameworks across personas (CIO, CTO, CRO, CDO) Articulate why an Enterprise AI Operating System is fundamentally different from AI tools or platforms Ensure consistency of narrative across all channels 2. Analyst & Market Engagement Support engagement with firms like Gartner and Forrester Prepare analyst briefings, narratives, and follow-ups Map product capabilities to analyst frameworks and categories Track analyst feedback and incorporate into positioning 3. Go-To-Market Strategy Define GTM plans for key markets, especially the US Partner with sales to build persona-led outreach narratives Shape campaign strategy with clear messaging direction Drive launch strategies for new capabilities and use cases 4. Campaign Narrative & Messaging (Email, Ads, Outreach) Define the narrative and messaging for: Email campaigns and outreach sequences LinkedIn and digital ad campaigns Account-based marketing efforts Develop persona-specific messaging flows and hooks Ensure campaigns reflect category positioning, not generic product marketing Work closely with growth and demand teams to guide execution and optimization 5. Content & Thought Leadership Develop high-impact assets: Whitepapers POVs and industry narratives Case studies Sales enablement content Elevate all content to US enterprise standards 6. Competitive & Market Intelligence Build and maintain competitive positioning Create battlecards and differentiation frameworks Identify whitespace and category opportunities Track trends in AI, GenAI, and enterprise adoption 7. Sales & Internal Enablement Equip sales with clear, differentiated messaging Create pitch narratives, talk tracks, and outreach frameworks Ensure internal alignment on positioning and story What You Should Bring 5–7 years of experience in Product Marketing Proven experience in B2B SaaS or enterprise technology environments Hands-on experience in: Positioning and messaging Go-to-market launches Working with or selling into enterprise buyers Strong ability to translate complex technical concepts into clear business value Experience shaping messaging for campaigns, outreach, or content Strong cross-functional collaboration across product, sales, and marketing Excellent writing and communication skills Good to Have Experience in early-stage or scaling startup environments Exposure to analyst relations or enterprise research firms Experience in AI, data, or deep tech domains Familiarity with regulated industries such as BFSI What Makes You a Strong Fit You think in categories, not features You can build narratives that scale across campaigns and channels You understand how messaging connects to pipeline and revenue You are comfortable working with senior stakeholders You bring both strategic thinking and execution depth ---------------------------------------------------------------------------------------------------------------------------------------- About DSW - Data Science Wizards (DSW) is building UnifyAI OS - the Enterprise AI Operating System (AI OS) for regulated and hybrid enterprises. As AI moves from experimentation into execution-especially with the rise of agentic systems- enterprises face a fundamental question: How do we build, deploy, operate, and govern AI continuously, safely, and at scale as part of the enterprise itself? DSW Enterprise AI OS enables enterprises to: • Build, integrate, deploy, orchestrate, govern, monitor, and continuously operate AI/ML and agentic workloads • Treat AI use cases, AI workloads, and AI applications as long-running production systems • Enforce governance-as-code at runtime, not through static policy documents • Retain full ownership of all AI artifacts and source code • Run AI entirely inside customer-controlled environments (on-premises, local, private cloud, hybrid) • Integrate a broad AI ecosystem without vendor lock-in DSW is defining a new AI category: Enterprise AI Operating Systems.