Software Architect, AI/ML
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Key skills for this role
About the Role
Autodesk seeks a Software Architect for AI/ML to design and build cloud-native AI agents for PDM/PLM workflows. The role involves architecting scalable services, defining model strategy, and setting technical direction.
Key Skills for This Role
Responsibilities
- Architect and build scalable, secure cloud native services and Agentic AI workflows that run in production
- Own the GenAI/ML architecture for production agentic systems: tool use, orchestration, state/memory, routing, and multi step workflows
- Define model strategy across prompting, retrieval (RAG), and fine tuning—making tradeoffs using measurable quality, latency, safety, and cost
- Standardize tool/context integrations across internal systems using MCP based patterns (or equivalent approaches)
- Establish evaluation + observability standards (regression tests, monitoring, feedback loops)
- Set technical direction via reference architectures, best practices, and hands on technical guidance across teams
- Partner closely with Product, Security/Privacy, and Engineering leaders to deliver high impact features
Requirements
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or equivalent practical experience
- 8+ years building cloud native software in production (distributed systems, APIs, data intensive services, reliability and operations)
- 4+ years delivering AI/ML powered systems in production
- Experience with 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 deploying and maintaining AI Applications in production reliably, monitoring performance, and improving over time
- Proficiency in Python/TypeScript/Java with strong engineering fundamentals
- Strong communication skills to explain tradeoffs and influence decisions
Full Job Posting
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.
Responsibilities
- Architect and build scalable, secure cloud native services and Agentic AI workflows that run in production
- Own the GenAI/ML architecture for production agentic systems: tool use, orchestration, state/memory, routing, and multi step workflows
- Define model strategy across prompting, retrieval (RAG), and fine tuning—making tradeoffs using measurable quality, latency, safety, and cost
- Standardize tool/context integrations across internal systems using MCP based patterns (or equivalent approaches), enabling teams to ship faster on a shared foundation
- Establish evaluation + observability standards (regression tests, monitoring, feedback loops)
- Set technical direction via reference architectures, best practices, and hands on technical guidance across teams
- Partner closely with Product, Security/Privacy, and Engineering leaders to deliver high impact features
Minimum Qualifications
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or equivalent practical experience
- 8+ years building cloud native software in production (distributed systems, APIs, data intensive services, reliability and operations)
- 4+ years delivering AI/ML powered system in production
- Traditional ML cloud applications (training pipelines, deployment, monitoring, iteration)
- 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)
- Strong communication skills: you can explain tradeoffs clearly and influence decisions without relying on authority
Preferred Qualifications
- Deep experience designing AI evaluation pipelines and production release strategies for AI Applications
- Experience with AWS/Azure/GCP and modern platform practices (containers, Kubernetes, CI/CD, observability)
- Experience in PLM/PDM, manufacturing, CAD, or enterprise workflow software
- Open source contributions, publications, or talks related to distributed systems, ML or GenAI systems
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