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# Software Engineer - Data and AI Services

- **Company:** Siemens AG
- **Location:** Parsippany-Troy Hills, NJ, United States (Remote available)
- **Experience:** Expert
- **Salary:** $193,461.0 - $207,809.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Adobe InDesign, Artificial Intelligence, Amazon Web Services, Automation of Tests, Code Review, Information Systems, Distributed Systems, Fault Tolerance, Github, Python (Programming Language), Machine Learning, NoSQL, Queueing Systems, Redis, Azure Machine Learning, SQL Databases, Systems Integration, TypeScript, Cloud Platform System, Pytorch, Kotlin, Kubernetes, Information Technology, ONNX (Open Neural Network Exchange) Format, HuggingFace, Docker, Golang
- **Published:** October 17, 2026
- **Apply:** https://jobs.siemens.com/en_US/externaljobs/ApplicationMethods?folderId=526203

## About the Role

Requirements: Employer will accept a Bachelor's degree in Computer Science, Information Systems, Information Technology, or related field and 60 months of experience in job offered or in an Software Engineer -related occupation.

## Description

Duties: Design, develop, test, and maintain backend software services and distributed system components. Implement software features using Python, Go, and TypeScript in cloud-native environments. Build and maintain microservices, REST APIs, and service-oriented system components. Develop and integrate cloud infrastructure components using AWS, Kubernetes, Redis, PostgreSQL, S3, and Terraform. Integrate machine learning frameworks including PyTorch, HuggingFace, and ONNX Runtime into production systems. Conduct performance analysis, optimization, and fault-tolerance engineering for production systems. Write automated tests and contribute to CI/CD pipelines using GitHub Actions. Troubleshoot production issues, perform root-cause analysis, and implement reliability improvements. Participate in design reviews, code reviews, and architecture discussions., 1. Deploying AI/ML services using Python, Go, Kotlin/Java, or TypeScript.

 2. Integrating machine learning models and frameworks including PyTorch, Huggingface, Docker OR ONNX Runtime into production pipelines.
 3. Utilizing AWS, Kubernetes, Redis, message queues, or SQL/NoSQL databases to build cloud infrastructures.
 4. Working with distributed systems and cloud-based software solutions.