Principal Knowledge Acquisition Analyst
Job Requisition ID #
26WD97787
Position Overview
Autodesk ’s Technical Advisory organization is building a scalable knowledge platform that transforms implementationexpertisefrom enterprise engagements into structured, reusable, and customer-facing guidance within Workflow Advisory.
The PrincipalKnowledge Acquisition Analystis responsible fordesigning andoperatingthe systems that capture and transform knowledge from consulting engagements. This includes building AI-powered extraction and transformation pipelines and ensuring raw implementation data is converted into structured, template-aligned outputs ready for downstream content production.
Reporting to the Senior Manager, Content & Knowledge, you willoperateat the intersection of consulting delivery, data, and AI systems. You will own the upstream knowledge pipeline—from extracting implementation intelligence to delivering high-quality structured inputs aligned to the content model.
In the first year, you willestablishscalable AI-assisted capture and transformation pipelines and ensure knowledge is reliably converted into reusable, high-quality outputs.
Responsibilities
Knowledge Capture and AI Pipelines
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Design andoperateAI-powered pipelines to capture knowledge from enterprise systems, meeting transcripts, and engagement artifacts
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Define and evolve the conceptual knowledge model, including key entities, relationships, and ontology governancerequiredto organize and retrieve implementation knowledge at scale
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Manage andoptimizeAI agents, including prompt design, evaluation, and performance tuning
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Define content-type-specific chunking strategies for consulting artifacts and work with Engineering to implement retrieval-ready knowledge structures
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Define requirements andparticipatein embedding and vectorization evaluation to ensure captured knowledge can be effectively discovered through semantic search and AI-powered retrieval
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Define and track quality metrics (accuracy, completeness, error rates) and continuously improve pipeline performance
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Ensure secure handling of sensitive information, including automated redaction and compliance with governance standards
Knowledge Transformation and Structured Ingestion
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Design andoperatepipelines that convert raw, unstructured inputs into structured, template-aligned outputs using AI
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Map extracted knowledge to defined content model fields, ensuring outputs are complete, consistent, and production-ready
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Define structured capture methods (forms, schemas, workflows) to ensure key context (decisions, constraints, trade-offs) is captured
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Normalize and standardize data across sources andidentifygaps to improve capture and transformation processes
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Define entity resolution and canonicalization rules to ensure concepts, terminology, and implementation knowledge are consistently represented across sources
Quality, AIReadinessand Integration
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Ensure structured outputs support AI-driven use cases including vector search, retrieval-augmented generation (RAG), knowledge graph navigation, and downstream content generation
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Partner with the Content ModelLeadto align transformation outputs with templates and structures
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Collaborate with Architecture and Engineering to align knowledge models, retrieval pipelines, and platform data models
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Define evaluation criteria for retrieval effectiveness, semantic relevance, and answer quality, and continuously improve knowledge performance through measurement and experimentation
Minimum Qualifications
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8+ years of experience in knowledge management, information architecture, information systems, semantic technologies, data engineering, or related field
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Experience working with AI/LLM-based workflows in production
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Experience designing data pipelines, structured capture, or transformation processes
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Strong analytical skills with ability to define and improve quality metrics
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Experience working cr