AI Builder - Distinguished Engineer

Autodesk•Portland, OR

About The Position

This is a role for an experienced engineer who wants to fundamentally change how systems work. You will join a small, AI-native disrupt squad within Autodesk’s Platform Services & Emerging Technologies (PSET) organization, accountable for redefining how the platform is experienced, accessed, and built upon. You won’t be handed well-defined problems. You will identify high-leverage opportunities, define what should exist, and prove a dramatically better way through working systems, using internal or external approaches. Your role is not just to make ideas real, but to determine where to focus and what matters most, building proof points that are viable, scalable, and capable of reshaping the platform. This team does not operate in traditional roles. As an AI Builder, you bring product thinking, experience design, and engineering together in one motion, shaping workflows end-to-end. You use AI, real systems, and rapid experimentation to reshape how work gets done and to determine which approaches truly deliver the best outcomes. Your focus is not on operating production systems. You are accountable for turning friction into opportunity and delivering near-production-grade proofs that make a new approach credible and hard to dismiss, shaping platform direction through those outcomes.

Requirements

10+ years of experience building and operating production systems, with demonstrated accountability for technical direction and outcomes across multiple teams or platform areas
Strong system and architectural judgment across services, data, and workflows
Strong applied AI capability (structuring problems for agents, orchestrating tools and workflows, evaluating outputs)
Strong product and workflow judgment with a focus on leverage and outcomes
Strong software engineering fundamentals and ability to build end-to-end systems across the stack
Experience operating in both startup and enterprise contexts, with demonstrated ability to adapt pace and approach accordingly
Proven ability to independently define where to focus, identify high-leverage problems, and drive them from ambiguity to working systems
Demonstrated ability to deliver cross-team or organizational impact, not just local features
Strong influence with senior stakeholders and ability to translate proof into direction

Nice To Haves

Experience working on AI-enabled systems or workflows in real-world environments
Hands-on experience building or orchestrating agent-based systems and tool integrations
Experience comparing multiple approaches to determine what actually works in practice
Experience working across SaaS platform business models, including familiarity with how platform economics and product adoption dynamics interact
Experience creating reusable patterns that influence how multiple teams build

Responsibilities

Identify and work through seams and bottlenecks across platform workflows, focusing on the highest-leverage opportunities where a different approach creates outsized impact across the platform
Define and build end-to-end, AI-native workflow proofs that turn fragmented systems into functioning, real-world workflows
Build production-like implementations that prove what works in practice, not just in concept
Use the right combination of tools, agents, and integrations to demonstrate materially better ways of working
Test and compare approaches in real workflows, challenging whether existing capabilities should be replaced, simplified, or rethought
Create undeniable proof points for AI-native workflows that expose gaps, challenge assumptions, and shape platform priorities and roadmap decisions across teams
Translate successful approaches into reusable patterns that can be adopted and scaled by other teams
Ensure high-impact approaches propagate across the platform, influencing what gets built, prioritized, or deprioritized
Bring perspective on how best-in-class SaaS platforms expose capabilities to internal and external builders
Evaluate trade-offs and risks when using external or non-standard solutions, ensuring new approaches can scale responsibly within evolving constraints