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# AI Software Integration Engineer

- **Company:** OSI Engineering
- **Location:** San Diego, CA, United States
- **Experience:** Experienced
- **Salary:** $120,640.0 - $151,840.0
- **Contract:** Temporary contract
- **Skills:** Microsoft Word, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Computer Engineering, JSON, Python (Programming Language), Parsing, Requirements Management, Requirements Traceability, Systems Integration, Extensible Markup Language (XML), Google Cloud, Large Language Models, Generative AI, Backend, Kubernetes, Information Technology, Integration Frameworks, Restful APIs, Webhooks, Docker
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/ac589891-b191-45b1-af1e-0b6550c33461

## About the Role

* M.S. or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience
 * 3-5 years of experience developing automation or integration tools in production environments
 * Strong understanding of generative AI models, particularly large language models (LLMs)
 * Experience designing and deploying agentic AI systems end-to-end
 * Familiarity with Agentic Development and surrounding technologies such as RAG & MCP
 * Familiar with AI-native workflow automation through Skills-based systems
 * Proficiency developing backend or automation services (Python preferred)
 * Experience integrating tools or databases using REST APIs or webhooks
 * Familiarity with structured document parsing (Word, PDF, XML, JSON, etc.)
 * Experience with CI/CD pipelines and automated testing frameworks
 * Understanding of requirements management and validation workflows

Bonus Qualifications:

 * Experience with NLP or text-processing automation
 * Knowledge of Cloud Platforms (AWS, Azure, or Google Cloud Platform)
 * Experience with Containers and Orchestration (Docker, Kubernetes, etc.)
 * Strong problem-solving skills with a passion for tackling new challenges

## Description

* Develop integration and automation solutions for engineering and validation workflows.
 * Build backend tools and services.
 * Automate test generation.
 * Improve requirements traceability.
 * Optimize workflows across multiple teams.


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