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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 Design andoperateAI-powered pipelines to capture knowledge from enterprise systems, meeting transcripts, and engagement artifacts Define and evolve the conceptual knowledge model, including key entities, relationships, and ontology governancerequiredto organize and retrieve implementation knowledge at scale Manage andoptimizeAI agents, including prompt design, evaluation, and performance tuning Define content-type-specific chunking strategies for consulting artifacts and work with Engineering to implement retrieval-ready knowledge structures
Define requirements andparticipatein embedding and vectorization evaluation to ensure captured knowledge can be effectively discovered through semantic search and AI-powered retrieval
Define and track quality metrics (accuracy, completeness, error rates) and continuously improve pipeline performance
Ensure secure handling of sensitive information, including automated redaction and compliance with governance standards
Knowledge Transformation and Structured Ingestion
Design andoperatepipelines that convert raw, unstructured inputs into structured, template-aligned outputs using AI
Map extracted knowledge to defined content model fields, ensuring outputs are complete, consistent, and production-ready
Define structured capture methods (forms, schemas, workflows) to ensure key context (decisions, constraints, trade-offs) is captured
Normalize and standardize data across sources andidentifygaps to improve capture and transformation processes
Define entity resolution and canonicalization rules to ensure concepts, terminology, and implementation knowledge are consistently represented across sources
Quality, AIReadinessand Integration
Ensure structured outputs support AI-driven use cases including vector search, retrieval-augmented generation (RAG), knowledge graph navigation, and downstream content generation Partner with the Content ModelLeadto align transformation outputs with templates and structures Collaborate with Architecture and Engineering to align knowledge models, retrieval pipelines, and platform data models
Define evaluation criteria for retrieval effectiveness, semantic relevance, and answer quality, and continuously improve knowledge performance through measurement and experimentation
Minimum Qualifications
8+ years of experience in knowledge management, information architecture, information systems, semantic technologies, data engineering, or related field
Experience working with AI/LLM-based workflows in production
Experience designing data pipelines, structured capture, or transformation processes
Strong analytical skills with ability to define and improve quality metrics
Experience working cross-functionally with product, engineering, and domain experts
Experienced in using technologies such as
Knowledge management platforms: Confluence, SharePoint, Notion Enterprise, Gainsight Knowledge, Guru
AI / LLM : OpenAI / AzureOpenAI , Anthropic Claude, Google Gemini
Agentic Workflow & Orchestration: ReAct (Reason + Act), Chain of Thought (CoT) patterns
AI Operations: Prompt design and evaluation, LLM output evaluation and benchmarking, Model monitoring and QA, RAG evaluation frameworks (e.g., RAGAS), retrieval observability tools (e.g.,LangSmith,TruLens), Vector Databases, Markdown files
AI Extraction & Document Processing: Unstructured.io,LlamaParse, document intelligence and content extraction platforms
Cloud environments: Azure, AWS, Google
The Ideal Candidate
Has built AI-driven knowledge capture or data pipelines at scale
Can transform messy, real-world data into structured, usable outputs
Thinks systemically about data, content, and downstream use
Works effectively across technical and non-technical teams
Focuses on building practical, scalable systems
Learn More
About Autodesk
Welcome to Autodesk ! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesk er, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary transparency
Salary is one part of Autodesk ’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
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