Principal Embedded Engineer, AI Solutions
Role Overview
Join Autodesk Technical Advisory's Embedded Engineering team, working directly with strategic customers on high-value workflows and AI systems for Design & Make workflows.
Work from customer workflow and architecture discovery through production code, building agents, orchestration, retrieval and graph services, connectors, and APIs inside customer environments.
Deliver AI agents, MCP servers and tools, domain and semantic models, knowledge-graph extensions, retrieval pipelines, and integrations with ERP, PLM, BIM, and enterprise data platforms.
Translate customer insights into reusable engineering assets and product feedback that can shape Autodesk's platform roadmap.
The engagement-driven role involves travel up to 75% during active engagements, including extended onsite periods with customers.
Key Skills for This Role
Full Job Posting
Position overview
Join Autodesk Technical Advisory's Embedded Engineering team, working directly with strategic customers on high-value workflows and AI systems for Design & Make workflows.
Work from customer workflow and architecture discovery through production code, building agents, orchestration, retrieval and graph services, connectors, and APIs inside customer environments.
Deliver AI agents, MCP servers and tools, domain and semantic models, knowledge-graph extensions, retrieval pipelines, and integrations with ERP, PLM, BIM, and enterprise data platforms.
Translate customer insights into reusable engineering assets and product feedback that can shape Autodesk's platform roadmap.
The engagement-driven role involves travel up to 75% during active engagements, including extended onsite periods with customers.
Workflow discovery and delivery
- Translate customer transformation objectives, operational KPIs, sustainability commitments, and digital initiatives into measurable AI-enabled workflow outcomes.
- Identify high-value workflows, decision bottlenecks, data requirements, and integration opportunities with customer teams.
- Analyze Autodesk and non-Autodesk workflows to find friction, inefficiency, data gaps, and useful AI opportunities.
- Own technical execution from rapid prototype through architecture, implementation, integration, testing, governance, deployment guidance, and adoption.
- Make explicit scope, speed, and durability trade-offs and explain decisions to stakeholders.
Data and context readiness
- Assess data sources, ownership, quality, lineage, metadata, governance, permissions, and integration constraints for trusted AI workflows.
- Structure design, project, product, and asset data and related requirements, evidence, approvals, decisions, and dependencies into AI-ready models.
- Design ontologies, semantic layers, and knowledge graphs, including entity resolution, schema mapping, and enterprise permission models.
Production AI engineering
- Build production-grade AI workflows, agents, applications, and integrations linking Autodesk products and platforms with enterprise technology environments.
- Build hybrid search, graph-grounded retrieval, tool interfaces, and MCP servers that provide agents with governed enterprise context.
- Create evaluation harnesses, golden datasets, guardrails, tracing, and observability to test agent behavior and monitor quality and drift.
- Apply strong practices for architecture, code quality, security, permissions, reliability, observability, testing, performance, and maintainability.
Candidate profile
- Strong software and AI engineering skills.
- Customer empathy, business judgment, and curiosity, with the ability to operate independently when problems are not yet well defined.
- Ability to travel up to 75% during active engagements, including extended onsite work with customers.
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