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.
