Principal Knowledge Automation Analyst

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

Knowledge Modeling & Semantic Technologies: Taxonomy and ontology management platforms (e.g., Semaphore,PoolParty), knowledge graphs, entity resolution and semantic enrichment tools, graph exploration platforms (e.g., Neo4j Bloom)

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

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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 Autodesker, 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. For Poland based roles, we expect a starting base salary between 187,500 PLN and 275,000 PLN. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Sales Careers

Working in sales at Autodesk allows you to build meaningful relationships with customers while growing your career. Join us and help make a better, more sustainable world. Learn more here: https://www.autodesk.com/careers/sales

Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

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