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# Principal Software Engineer

- **Company:** Siemens AG
- **Location:** Wilsonville, OR, United States
- **Experience:** Expert
- **Salary:** $154,200 - $277,600
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computer Vision, Automation of Tests, C++ (Programming Language), Computer Programming, Data Structures, Distributed Systems, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Knowledge Management, Machine Learning, Performance Tuning, Software Architecture, Inference Optimization, Software Tools, Scientific Computating, Software Engineering, Software Systems, Retrieval-Augmented Generation, Large Language Models, Agentic-AI, Information Technology, Machine Learning Operations
- **Published:** November 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=8abf1c4af6038720

## About the Role

A bachelor's, master's, or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related technical field.

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A minimum of 10 years of professional software engineering experience, including substantial hands-on experience developing and deploying AI or machine learning capabilities.

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Demonstrated technical leadership in designing and delivering complex, production-quality software systems.

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Strong programming skills in Python and C++, with experience developing in Unix/Linux environments.

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Practical experience with modern AI frameworks and applying machine learning, large language models, or generative AI to real-world problems.

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Experience integrating AI models with software tools, APIs, data sources, and application workflows.

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Strong understanding of software architecture, algorithms, data structures, automated testing, and performance optimization.

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Ability to evaluate AI system behavior, diagnose failures, and improve quality through systematic testing and measurement.

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Strong written and verbal communication skills, with the ability to collaborate across disciplines and guide technical decisions.

Preferred Qualifications
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Experience with agent orchestration, tool calling, retrieval-augmented generation, or knowledge management systems.

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Experience with model serving, inference optimization, GPU computing, or distributed systems.

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Familiarity with model adaptation, fine-tuning, computer vision, or scientific computing.

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Experience deploying AI solutions in enterprise or customer-controlled environments.

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Familiarity with semiconductor manufacturing, EDA, inspection, metrology, or other complex engineering domains.

## Description

We are seeking a Principal Software Engineer with strong expertise in artificial intelligence and software architecture to help develop the next generation of intelligent engineering software.
In this role, you will lead the design and development of AI-powered capabilities that automate complex workflows, improve engineering productivity, and turn domain expertise into reliable, scalable software. You will work closely with engineering, product management, and customer teams to translate emerging AI technologies into production-ready solutions across the Siemens EDA portfolio.
This position requires hands-on engineering, sound architectural judgment, and the ability to guide technical direction and mentor engineers., Intelligent Workflow Automation: Build AI agents that use software tools, APIs, and domain knowledge to execute tasks, validate results, and support human oversight.

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Production Engineering: Advance AI capabilities from experimentation to deployment, emphasizing maintainability, scalability, performance, and reliability.

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Evaluation & Quality: Establish testing and evaluation approaches for AI systems, including task success, accuracy, robustness, reproducibility, and operational performance.

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Product Definition & Strategy: Partner with product management and domain experts to identify valuable AI use cases, define requirements, and guide technical roadmaps.

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Cross-Functional Collaboration: Work with software, infrastructure, research, and customer teams to integrate and deploy AI capabilities within existing products and platforms.

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Technical Leadership: Lead architecture and design reviews, establish engineering standards, mentor engineers, and resolve complex technical challenges.

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Research & Innovation: Evaluate emerging AI technologies and make practical build-versus-adopt decisions based on product needs and engineering evidence.