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Senior Software Developer (Applied GenAI – DevX)
Autodesk
Design and make software for architecture, engineering, construction, and entertainment industries.
Develop AI-driven agentic systems to boost developer productivity at Autodesk.
Design and implement agentic workflows that coordinate multiple AI agents for complex development tasks, ensuring seamless integration with existing developer tools
Effective collaborator with engineers and stakeholders to drive outcomes
Develop statistical models for developer behavior analysis, workflow optimization, and productivity measurement with measurable KPIs
Work with extensive code datasets, developer interaction data, and multi-modal development artifacts (code, documentation, UI) from integrated productivity tools
Develop and orchestrate multi-agent AI systems for automated code review, test generation, continuous integration, and end-to-end development workflow optimization using frameworks like LangGraph and AutoGen
Deploy models in production while adhering to responsible AI principles and Autodesk model governance standards, and mentor junior software AI engineers
Build comprehensive evaluation frameworks and custom benchmarks for agentic systems, through A/B testing and specialized tools like AgentBench and Langfuse
What you bring
python
git
ci/cd
azure
phd
nlp
Proven ability to build end-to-end ML solutions, from research to production
Experience with developer workflow and productivity measurement frameworks
Familiarity with software development lifecycle tools (e.g., Git, GitHub/GitLab APIs, CI/CD pipelines)
Expertise in Python and ML frameworks (PyTorch, Transformers, scikit-learn)
Approach problems with curiosity, iterate quickly, and aren't afraid to experiment
Knowledge of human-computer interaction principles and developer experience best practices
MS/PhD in Computer science, Machine Learning, or a related applied AI field
Proficiency in multiple programming languages (Java, C++ or Python)
Experience with Azure AI Foundry/ML or AWS cloud ML platforms
Comfortable working in ambiguous, rapidly evolving areas
Background in software engineering or close collaboration with development teams
5+ years of experience in machine learning with a focus on NLP, code analysis, or developer tools
Strong foundation in statistical analysis, experimental design, and A/B testing
Hands-on experience with agentic AI frameworks and evaluation frameworks
Constant learner of new technologies in AI and developer tools
Knowledge of AI evaluation methodologies and specific metrics for code generation
Experience with Large Language Models and code generation models
Research publications or contributions to open-source projects in code intelligence or developer productivity
Experience with vector databases and embedding strategies for code search and similarity
Knowledge of code analysis tools and techniques (e.g., AST parsing or Tree-sitter)
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