Torchora
Back to Home

Key Responsibilities and Required Skills for Knowledge Strategist Assistant

💰 $ - $

🎯 Role Definition

The Knowledge Strategist Assistant supports the strategic design, implementation, and optimization of an organization’s knowledge ecosystem. Working closely with Knowledge Strategists, Knowledge Managers, Product and Engineering teams, and business stakeholders, this role drives content lifecycle management, taxonomy and metadata governance, knowledge base health, and applied AI techniques (semantic search, embeddings, RAG, LLM prompt optimization) to increase findability, reduce support friction, and improve organizational learning. This is a hands-on, cross-functional role that blends content operations, information architecture, analytics, and stakeholder enablement.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Knowledge Management Coordinator / Specialist
  • Content Operations Associate or Technical Writer
  • Customer Support Knowledge Analyst

Advancement To:

  • Knowledge Strategist / Knowledge Manager
  • Senior Knowledge Engineer or Knowledge Architect
  • Head of Knowledge, Director of Knowledge Operations, or Product Manager (Knowledge Platform)

Lateral Moves:

  • Content Strategy
  • Information Architecture / UX Content
  • Customer Success Operations

Core Responsibilities

Primary Functions

  • Partner with the Knowledge Strategist to develop and maintain a comprehensive knowledge strategy that aligns content, taxonomy, and search with business objectives such as reduced support tickets, improved time-to-answer, and higher self-service success rates.
  • Conduct regular knowledge audits and content gap analyses across help centers, internal wikis, FAQ pages, and product documentation to identify obsolete content, duplication, and opportunities for consolidation.
  • Design, maintain, and enforce content taxonomy and metadata schemas that improve information findability, enable semantic search, and support multi-channel delivery (web, in-product help, chatbot).
  • Drive knowledge base content lifecycle management including authoring standards, version control, archival policies, and content retirement workflows to keep knowledge current and trustworthy.
  • Implement, tune, and monitor semantic search and relevance systems (including vector search/embeddings) to maximize retrieval precision and recall for both internal stakeholders and customer-facing search.
  • Support development and deployment of Retrieval-Augmented Generation (RAG) and LLM-enhanced assistive agents by curating high-quality source documents, creating safe retrieval pipelines, and testing prompt/response behaviors for accuracy and alignment.
  • Create and maintain comprehensive documentation and playbooks for content contributors, subject-matter experts (SMEs), and moderators to ensure consistent article quality, tone, and taxonomy application.
  • Collaborate with product, engineering, and ML teams to map content to knowledge graphs, ontologies, and structured data schemas that support personalization, recommendation, and intelligent assistance features.
  • Lead or assist content migration and consolidation projects, including planning migrations between CMS/KB platforms, validating content integrity, and minimizing SEO and link equity loss.
  • Implement a governance framework for knowledge ownership, approval workflows, SLAs for updates, and compliance checks for regulated content or user data confidentiality.
  • Monitor and report on knowledge performance using KPIs such as search success rate, deflection rate, time-to-first-answer, article usefulness, and user feedback to drive continuous improvement.
  • Build dashboards and analytics pipelines (using BI tools or analytics suites) to visualize knowledge health, user journeys, and search behavior for stakeholders and executive reporting.
  • Facilitate cross-functional working groups and stakeholder interviews to collect requirements, prioritize knowledge initiatives, and ensure alignment between business goals and knowledge operations.
  • Conduct user research and usability testing for search, article layouts, and in-product help flows to refine information architecture and content presentation.
  • Train and onboard support agents, SMEs, and community moderators on best practices for content creation, tagging, and escalation processes to improve quality and speed of updates.
  • Establish and execute multilingual knowledge strategies including translation workflows, localization quality checks, and region-specific content governance.
  • Perform content QA, metadata audits, and relevance testing to reduce noise, improve signal-to-noise ratio, and proactively correct incorrect or outdated answers surfaced by automated assistants.
  • Evaluate and pilot knowledge tooling and vendors (KM platforms, search engines, vector DBs, chatbot platforms) and help craft vendor selection criteria and ROI cases.
  • Help operationalize privacy, security, and ethical guardrails for AI-assisted knowledge products including PII redaction, source attribution, and hallucination mitigation protocols.
  • Maintain and evolve a library of reusable prompts, retrieval templates, and answer templates to standardize LLM interactions and improve response consistency across channels.
  • Support agile delivery processes for the knowledge team; write requirements, acceptance criteria, and user stories; and participate in sprint planning to deliver incremental knowledge improvements.
  • Proactively surface insights from support trends, product telemetry, and community channels to recommend content or product changes that reduce repetitive inquiries and improve user satisfaction.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Assist with vendor management logistics including contracts, onboarding, and solution configuration as required by knowledge initiatives.
  • Create internal communications and training collateral to drive KM adoption and awareness across the organization.
  • Maintain a backlog of content improvement tasks and coordinate with editors and subject matter experts for prioritization.
  • Provide escalation support for complex knowledge incidents or search regressions until resolution.

Required Skills & Competencies

Hard Skills (Technical)

  • Knowledge Management Systems: practical experience with knowledge bases and CMS platforms (e.g., Confluence, SharePoint, Zendesk Guide, HelpCenter tools, Guru, Bloomfire) and content migration best practices.
  • Information Architecture & Taxonomy Design: ability to design hierarchical taxonomies, metadata schemas, and tagging strategies that improve findability and indexing.
  • Semantic Search & Vector Technologies: familiarity with embeddings, vector databases (e.g., Pinecone, Milvus, FAISS), and techniques for semantic retrieval and hybrid search.
  • LLM & RAG Integration: hands-on knowledge of retrieval-augmented generation workflows, prompt libraries, source attribution, and evaluation of LLM outputs for factuality and safety.
  • Knowledge Graphs & Ontologies: experience mapping content to graph structures, creating entity relationships, and supporting linked data use cases.
  • Analytics & BI: proficiency with analytics tools (Google Analytics, Mixpanel, Amplitude) and BI/dashboarding (Looker, Power BI, Tableau) to measure content impact and user behaviors.
  • Search Relevance Tuning: experience with relevance ranking, query understanding, synonyms, stop words, and boosting rules in search engines (e.g., Elasticsearch, Algolia).
  • Content Authoring & Editing: strong technical writing skills, style guide enforcement, and ability to convert technical content into user-friendly documentation.
  • Data Governance & Compliance: knowledge of privacy requirements (GDPR, CCPA), redaction techniques, and governance processes for sensitive content used in AI/assistive systems.
  • QA & Testing Frameworks: competency in defining test cases for content accuracy, search relevance, and regression testing for knowledge-driven features.
  • Basic Scripting & Data Manipulation: comfort with CSV/data transforms, regular expressions, and simple scripting (Python, SQL) to clean, tag, and migrate content.
  • Project Management & Agile Tools: experience writing user stories, managing backlog items, and using tools such as JIRA, Trello, or Asana.

Soft Skills

  • Cross-functional Collaboration: able to build trust and partner productively with engineering, product, support, and legal teams.
  • Communication & Influence: clear presenter and writer who can evangelize KM best practices and gain stakeholder buy-in.
  • Analytical Mindset: strong problem-solving skills with the ability to translate data and user feedback into actionable improvements.
  • Attention to Detail: meticulous with metadata, taxonomies, and content quality to ensure high trust in knowledge outputs.
  • Curiosity & Continuous Learning: eagerness to stay current on KM trends, search tech, and LLM capabilities and to iterate quickly.
  • Customer Empathy: focus on user-first outcomes and ability to balance business goals with end-user needs.
  • Prioritization & Time Management: comfortable juggling multiple initiatives and driving toward measurable outcomes.
  • Coaching & Enablement: experience training SMEs and support teams to scale content creation and governance.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Information Science, Library Science, Communication, Technical Writing, Computer Science, or a related field; OR equivalent practical experience in knowledge operations or content strategy.

Preferred Education:

  • Master's degree or advanced certification in Knowledge Management, Information Architecture, Human-Computer Interaction, Data Science, or related disciplines.

Relevant Fields of Study:

  • Information Science / Library & Information Studies
  • Technical Communication / Journalism
  • Computer Science / Human-Computer Interaction
  • Data Analytics / Business Intelligence
  • Knowledge Management / Organizational Learning

Experience Requirements

Typical Experience Range:

  • 2–5 years in knowledge operations, content strategy, technical writing, or knowledge engineering roles; or equivalent cross-functional experience supporting KM and search initiatives.

Preferred:

  • 3–7 years working with KM platforms, search technologies, and/or AI-assisted knowledge systems; demonstrated impact on self-service adoption, deflection metrics, or search relevance improvements.
Explore More Careers