Senior Software Engineer-AI/ML

Job Description

Position Overview

If you love building real systems that real customers useand you get genuinely excited about LLMs, RAG, MCP, and agentic architecturesthis role is for you.

The Applied AI team in Autodesks 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 youll design core platform patterns and also write code that lands in production.

Were looking for a modern builder: Ambitious, Curious, and Practicalsomeone 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 documentationbut 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 patterns

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

Bachelors or Masters 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 SageMaker for scalable training and deployment

Contributions to open-source AI projects or publications in the field

Experience with emerging Agentic AI solutions such as LangGraph, CrewAI, A2A, Opik Comet, or equivalents.

#LI-KS2