Product Platform Knowledge Expert / Strategist (Architects Preferred)

Responsibilities

OPUS Platform Domain Expertise

• Serve as TraceLink's subject-matter expert for the OPUS Platform, supporting Product Marketing, Demand Generation, Content, Sales Enablement, and Sales teams.
• Build a deep understanding of OPUS Platform architecture and capabilities, and how the platform enables TraceLink solutions and customer business outcomes.
• Translate complex platform concepts into clear business value for executive, technical, and operational personas.
• Participate in select cross-functional initiatives, roadmap discussions, and executive or customer engagements as required.

Strategic Narratives, Messaging, and Positioning

• Develop strategic narratives, messaging, and positioning for the OPUS Platform targeting executive and technical decision-makers (e.g., CIO, CDO, CTO, Enterprise Architects).
• Articulate the OPUS Platform value proposition as the foundation for TraceLink solutions, ecosystem participation, and digital network effects.
• Create and maintain competitive differentiation against alternative platforms, point solutions, and legacy integration approaches.
• Continuously validate and refine messaging through regular engagement with field teams, customers, and prospects.

AI and LLM Buying & Enablement Experiences

• Build and maintain an LLM-ready OPUS Platform messaging framework with modular, metadata-tagged positioning, capabilities, and value narratives.
• Ensure taxonomy alignment, version control, and canonical terminology so platform messaging is consistent, current, and consumable by AI systems.
• Curate and govern the OPUS Platform knowledge corpus to ensure accurate, secure, and authoritative AI-generated outputs.
• Design executive- and architect-ready LLM experiences using prompt patterns, scenarios, and platform value-story templates for internal enablement and external buyer interactions.

Deliverables and Key Knowledge Artifacts

Create and maintain a standard set of OPUS Platform knowledge artifacts that drive executive conversations, field enablement, and LLM-driven experiences, including but not limited to:

• OPUS Platform Messaging & Positioning Playbook documenting platform vision, value pillars, persona-based messaging, and competitive differentiation.
• LLM-Ready Platform Messaging Framework & Metadata Schema defining modular platform message objects, taxonomies, and canonical terminology for AI ingestion.
• Curated OPUS Platform Knowledge Library, including architecture overviews, capability descriptions, platform services, extensibility patterns, security and compliance models, and glossary of terms.
• Executive Platform Narrative Decks tailored for CIO, CTO, CDO, and VP-level personas, highlighting business value, scalability, interoperability, and long-term platform ROI.
• Competitive Platform Landscape & Differentiation Dossiers comparing OPUS to alternative platforms, middleware, and integration strategies with scenario-based differentiation and objection handling.
• LLM Prompt Patterns, Conversation Flows, and Experience Blueprints enabling consistent, high-credibility AI-driven conversations about the OPUS Platform.
• Field Enablement Knowledge Packs including platform talk tracks, architecture narratives, use-case mappings, objection handling, and LLM-powered microlearning assets.

Skills and Qualifications

• 10+ years of experience in product management, product marketing, platform strategy, solution consulting, or analyst roles with exposure to enterprise platforms, data networks, or SaaS ecosystems.
• Strong understanding of platform concepts such as APIs, data models, interoperability, extensibility, security, and scalability.
• Exceptional writing and presentation skills, particularly for senior executive and technical audiences.
• Ability to distill complex, technical platform capabilities into clear, structured business narratives.
• Experience producing strategic content such as platform briefs, architecture narratives, whitepapers, or competitive analyses.
• Familiarity with large language models (LLMs), conversational AI, or retrieval-augmented generation (RAG) systems.
• Experience in structuring, tagging, and governing content for AI/ML consumption is a plus.
• Proven ability to work cross-functionally with Product, Engineering, Marketing, Sales, Solution Consulting, Value Engineering, and Services teams.
• Bachelor's degree or equivalent professional experience required.