Senior GenAI Engineer

26WD98447

Position Overview

If you love building real systems that real customers use-and you get genuinely excited about LLMs, RAG, MCP, and agentic architectures-this role is for you. The Applied AI team in Autodesk's AEC organization builds cloud-native AI solutions that make Architecture, Engineering, and Construction workflows smarter, faster, and more connected. Our mission is to bring AI-powered intelligence into construction management, BIM, project collaboration, document management, and digital delivery workflows used by customers worldwide.

This is a hands-on architecture and engineering role where you'll design core AI platform patterns and also write production-grade code that powers real customer experiences. We're looking for a modern builder: Ambitious, Curious, and Practical-someone who has already shipped scalable cloud-native AI applications into production and wants to help shape the future of AI in AEC.You may come from a strong GenAI background, or you may have built traditional ML systems (recommendations, forecasting, anomaly detection, optimization) at scale and are now moving deeper into agentic AI architectures. Either way, you build for reliability, quality, observability, and business impact.

AI-assisted engineering (how we deliver) We use modern AI coding agents (e.g., Cursor Agent, Claude Code, Codex, or similar) to accelerate planning, implementation, debugging, testing, and documentation-but engineers own correctness, security, scalability, and maintainability.

Responsibilities

• Build and ship production-grade cloud-native Agentic AI applications for AEC workflows that are resilient, performant, secure, and scalable

• Design AI-powered solutions for construction management, BIM workflows, project coordination, document intelligence, and engineering collaboration systems

• Fine-tune, evaluate, and deploy large language models in production environments

• Implement evaluation and observability standards including regression testing, monitoring, tracing, feedback loops, and quality measurement for AI systems

• Integrate AI agents with Autodesk platforms and enterprise services using MCP-based integrations or equivalent tool/context integration patterns

• Build scalable RAG pipelines using structured and unstructured AEC data sources such as project documents, RFIs, submittals, specifications, drawings, and knowledge repositories

• Partner with product managers, architects, developers, designers, and data scientists to deliver AI-powered experiences within Autodesk AEC products and platforms

• Contribute to reusable AI platform capabilities, SDKs, orchestration patterns, and engineering best practices

• AI-assisted delivery: Use AI coding agents to accelerate feature delivery and issue resolution while ensuring rigorous validation through tests, CI/CD, code reviews, and security practices

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or equivalent practical experience

• 5+ years building cloud-native software in production environments, including distributed systems, APIs, data-intensive applications, reliability, and operations

• 5+ years of hands-on experience delivering AI/ML-powered systems into production

• Traditional ML systems (training pipelines, deployment, monitoring, optimization), and/or

• LLM-based systems including RAG, MCP, agent workflows, orchestration frameworks, and fine-tuned models

• Experience with MCP or similar standardized patterns for connecting models to tools, enterprise systems, and contextual data

• Experience deploying and operating AI applications reliably in production, including monitoring, observability, performance tuning, and continuous improvement

• Strong proficiency in Python, TypeScript, or Java with solid engineering fundamentals including testing, performance optimization, security, and code quality

• Experience building cloud-native applications on AWS, Azure, or Google Cloud

• Excellent technical communication and documentation skills with the ability to collaborate across engineering, product, and domain teams

• Demonstrated experience using AI coding tools to accelerate delivery of production systems, along with strong engineering judgment to validate and improve AI-generated output

Preferred Qualifications

• Experience building AI applications for AEC, construction technology, BIM, digital twins, engineering collaboration, or project lifecycle management domains

• Familiarity with Autodesk Construction Cloud (ACC), BIM workflows, construction data ecosystems, or project management platforms

• Proven experience building scalable cloud-native AI applications using AWS, Azure, or Google Cloud platforms

• Familiarity with deep learning architectures such as Transformers and modern ML frameworks including PyTorch, Lightning, Ray, or equivalent technologies

• Hands-on experience with AWS services such as SageMaker, Bedrock, Lambda, ECS/EKS, OpenSearch, or vector databases for scalable AI deployment

• Experience with enterprise knowledge graph systems, semantic search, vector search, or contextual retrieval systems

• Experience with emerging Agentic AI frameworks and orchestration solutions such as LangGraph, CrewAI, A2A, MCP, OpenAI SDKs, Claude SDKs, or equivalent technologies

• Contributions to open-source AI projects, technical blogs, conference talks, or publications in AI/ML or cloud-native engineering

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About Autodesk

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