Software Engineer III

Job Title: Software Engineer III – AI Software Integration Engineer
Location: San Diego, CA (Hybrid)
Employment Type: Contract (9 Months)
Potential Extension: Up to an additional 4 months based on business needs and performance
Pay rate: $73/hr. on W2
 
Position Summary
We are seeking a highly skilled Software Engineer III – AI Software Integration Engineer to join our engineering team in San Diego. This role is focused on designing, developing, and deploying AI-driven integration and automation solutions that streamline engineering, validation, and operational workflows across multiple teams.
The ideal candidate will have hands-on experience with Generative AI, Large Language Models (LLMs), Agentic AI systems, workflow automation, and backend service development. This individual will collaborate with cross-functional engineering teams to build scalable tools that automate test generation, improve requirements traceability, enhance validation processes, and optimize overall team productivity.
This position offers a unique opportunity to work at the intersection of software engineering, AI innovation, and process automation within a fast-paced engineering environment.
 
Key Responsibilities

• Design, develop, and maintain AI-powered integration and automation solutions that improve engineering and validation workflows.
• Build backend services and tools that automate test generation, requirements verification, and workflow orchestration.
• Develop and deploy agentic AI systems leveraging LLMs and modern AI frameworks.
• Implement Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and other advanced AI integration technologies.
• Create AI-native workflow automation solutions using skills-based architectures and intelligent agents.
• Integrate internal and external tools, applications, and databases through REST APIs, webhooks, and other service interfaces.
• Develop solutions for structured document parsing and data extraction from formats such as Word, PDF, XML, JSON, and related document types.
• Collaborate with engineering, validation, and product teams to understand workflow challenges and implement scalable automation strategies.
• Support and enhance CI/CD pipelines while ensuring robust automated testing and deployment practices.
• Establish traceability between requirements, test cases, validation activities, and engineering documentation.
• Troubleshoot, optimize, and maintain existing automation frameworks and integration services.
• Document system designs, workflows, and technical implementations to support long-term maintainability.

 
Required Qualifications

• Strong understanding of Generative AI models, particularly Large Language Models (LLMs).
• Hands-on experience designing, developing, and deploying Agentic AI systems in production environments.
• Familiarity with emerging AI development concepts and technologies, including:
  • Retrieval-Augmented Generation (RAG)
  • Model Context Protocol (MCP)
  • AI orchestration frameworks
• Experience developing AI-native workflow automation solutions using skills-based systems.
• Proficiency in backend software development and automation engineering, with Python preferred.
• Experience integrating applications, services, tools, and databases using:
  • REST APIs
  • Webhooks
  • Service-based architectures
• Knowledge of structured document parsing and processing technologies.
• Experience with CI/CD pipelines and automated testing frameworks.
• Understanding of requirements management, validation processes, and engineering workflow optimization.
• Strong analytical, troubleshooting, and problem-solving capabilities.
• Excellent communication and collaboration skills.

 
Preferred Qualifications

• Experience with Natural Language Processing (NLP) applications and text-processing automation.
• Knowledge of cloud platforms such as:
  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform (Google Cloud Platform)
• Experience with containerization and orchestration technologies, including:
  • Docker
  • Kubernetes
• Experience working in highly collaborative engineering environments.
• Demonstrated ability to learn new technologies quickly and solve complex technical challenges.

 
Education & Experience

• Master’s degree or Ph.D. in:
  • Computer Science
  • Computer Engineering
  • Electrical Engineering
  • Related technical discipline

OR
Equivalent combination of education and relevant professional experience.

• 3 to 5 years of experience developing automation, integration, or backend software solutions in production environments.
• Proven experience delivering scalable software systems and workflow automation tools.

 
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