Principal Automation Analyst

Job Requisition  # 26WD97787

Autodesk’s Technical Advisory organization is building a scalable knowledge platform that transforms implementation expertise from enterprise engagements into structured, reusable, and customer‑facing guidance within Workflow Advisory.

The Principal Knowledge Engineer is responsible for designing and operating the 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 will operate at 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 will establish scalable AI‑assisted capture and transformation pipelines and ensure knowledge is reliably converted into reusable, high‑quality outputs.

• Design and operate AI‑powered pipelines to capture knowledge from enterprise systems, meeting transcripts, and engagement artifacts
• Manage and optimize AI agents, including prompt design, evaluation, and performance tuning
• 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

• Design and operate pipelines 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 and identify gaps to improve capture and transformation processes

• Ensure structured outputs support AI‑driven use cases such as retrieval (RAG) and downstream content generation
• Partner with the Content Model Lead to align transformation outputs with templates and structures
• Collaborate with Architecture and Engineering to align pipelines with platform data models
• Identify and resolve data quality issues and improve end‑to‑end system performance

• 8+ years of experience in knowledge management, data engineering, information systems, or related fields
• 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

• Knowledge management platforms:
  Confluence, SharePoint, Notion Enterprise, Gainsight Knowledge, Guru
• AI / LLM:
  OpenAI / Azure
  
  OpenAI, 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, Vector Databases, Markdown files
• Cloud environments:
  Azure, AWS, Google

• 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