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 Data and Process Management (DPM) organization ships Cloud-Native AI agents that make our Product Data Management (PDM) and Product Lifecycle Management (PLM) workflows smarter and easier.
This is a hands-on architecture role where you'll design core platform patterns and also write code that lands in production. We're looking for a modern builder:
Ambitious, Curious, and Practical—someone who has already shipped Scalable, Cloud-Native AI Applications to production and wants to level up further.
You might have expertise in GenAI Applications, or you might have shipped traditional Machine Learning applications (recommendations, forecasting, anomaly detection) at scale and are ready to go all-in on agentic architectures. Either way, you build for reliability, quality, and impact. AI-assisted engineering (how we deliver):
We use modern AI coding agents (e.g., Cursor Agent, Claude Code, Codex or similar) as accelerators for planning, implementation, debugging, and documentation—but you own correctness, security, and maintainability.
Responsibilities
Build and ship production-grade cloud-native Agentic AI applications that are resilient, performant, and can scale well in production
Fine-tune, evaluate, and deploy large language models in production environments
Implement evaluation + observability standards (regression tests, monitoring, feedback loops)
Integrate agents with internal/external services using MCP-based integrations or equivalent tool/context integration pattern
Partner with product managers, architects, developers, and data scientists to bring AI features to life in Autodesk products
AI-assisted delivery:
Use AI coding agents to accelerate delivery of production features and fixes, with rigorous verification (tests, CI, code review) and security-aware usage
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 (distributed systems, APIs, data-intensive services, reliability and operations)
2+ years of hands-on experience of delivering AI/ML-powered system in production
This can include:
Traditional ML cloud applications (training pipelines, deployment, monitoring, iteration), and/or LLM-based systems (RAG, MCP, Agent workflows, fine-tuned models)
Experience with MCP or similar standardized patterns for connecting models to tools and context
Experience with deploying and maintaining AI Applications in production reliably, monitoring performance, and improving over time
Proficiency in Python/TypeScript/Java with strong engineering fundamentals (testing, code quality, performance, security)
Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
Demonstrated experience using AI coding tools to ship production systems, and the engineering judgment to verify and correct AI output (code review rigor, debugging skill, ownership of correctness)
Preferred Qualifications
Experience building AI applications in the CAD or manufacturing domain
Proven track record of building and deploying scalable cloud-native AI applications using platforms like AWS, Azure, or Google Cloud
Familiarity with deep learning architectures (e.g., Transformers) and modern ML frameworks such as PyTorch, Lightning, and Ray
Hands-on experience with AWS and Sage Maker for scalable training and deployment
Contributions to open-source AI projects or publications in the field
Experience with emerging Agentic AI solutions such as Lang Graph, CrewAI, A2A, Opik Comet, or equivalents
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25WD94056, Développeur logiciel senior, IA/ML
Aperçu du Poste
Si vous appréciez la conception de systèmes réels utilisés par de véritables clients et que vous êtes passionné par les LLM, les RAG, les MCP et les architectures agencées, ce…
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