Sr Principal Applied AI Engineer

Autodesk is a company that empowers creative individuals by providing software tools for various industries, including construction. They are seeking a Senior Principal AI/ML Engineer to lead the development of AI applications that enhance construction workflows, focusing on multimodal AI and agentic systems.

Responsibilities:

• Define and lead technical strategy for multimodal and agentic AI capabilities across Autodesk Construction Cloud
• Drive the architecture and delivery of intelligent systems that combine NLU, retrieval, computer vision, multimodal reasoning, and agentic workflows
• Build and evolve AI applications that work across construction data such as specifications, drawings, RFIs, issues, submittals, schedules, meeting content, photos, and field observations
• Partner closely with Product, UX, Engineering, and domain stakeholders to identify high-value construction workflows and turn them into scalable AI features
• Shape the design of agentic systems that can retrieve, reason, summarize, recommend, and take workflow-aware actions in trusted and governed ways
• Lead the development of evaluation harnesses, benchmark suites, and quality frameworks for multimodal and agentic AI systems
• Help define how AI systems should behave in construction contexts, including grounding, evidence, permissions, traceability, fallback behavior, and human-in-the-loop controls
• Drive technical direction for reusable AI services and platform capabilities that can support multiple construction workflows and product surfaces
• Mentor senior and mid-level engineers, data scientists, and ML engineers, and help raise the bar for architecture, experimentation, engineering quality, and technical judgment
• Influence roadmap decisions through strong partnership with product leadership and by connecting technical investments to customer value and business outcomes
• Represent Construction in broader Autodesk AI platform conversations and help ensure construction workflows shape platform patterns and standards

Requirements:

• Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Data Science, Information Systems or equivalent industry experience
• At least 8 years of industry experience in software engineering, AI/ML systems, computer vision, applied AI, or related domains
• Proven track record of building and shipping AI or ML systems in the construction, AEC, BIM/VDC, project controls, field operations, or construction technology space
• Strong experience across multiple AI domains, including a combination of: natural language understanding or LLM applications, computer vision or multimodal AI, retrieval, search, or document intelligence, agentic workflows or orchestration systems
• Strong software engineering and systems design fundamentals, including production-quality implementation, APIs, cloud services, testing, observability, and operational reliability
• Demonstrated ability to work closely with Product and cross-functional partners to define requirements, evaluate tradeoffs, and ship high-impact customer-facing capabilities
• Demonstrated experience mentoring engineers, leading technical direction, and operating as a force multiplier across teams
• Strong communication skills and the ability to influence technical and non-technical stakeholders
• Experience building multimodal AI systems that connect text, drawings, images, site photos, metadata, and workflow context
• Experience with LLM applications, RAG, tool use, knowledge systems, agent orchestration, or MCP-style architectures
• Experience with computer vision techniques such as document understanding, image classification, detection, segmentation, visual grounding, OCR, or vision-language models
• Experience designing ML-ready representations for AEC data, including the ability to understand, structure, and choose appropriate representations for models working with complex design and construction data
• Experience designing evaluation frameworks for AI systems, including workflow quality, response quality, retrieval quality, precision, recall, latency, and trust metrics
• Experience with permissions-aware retrieval, governance, responsible AI practices, and evidence-based user experiences
• Experience building AI systems for construction workflows such as document management, specifications, submittals, issues, quality, safety, inspections, coordination, field reporting, preconstruction, or project controls
• Experience building shared services or platform capabilities that support multiple AI applications or teams
• Experience working with product managers and designers to translate domain pain points into shipped AI product capabilities
• Familiarity with construction ontologies, connected project data, BIM/CAD artifacts, and the operational realities of project delivery