AI Engineer - Information Technology
Job
Pond & Company
Peachtree Corners, GA (In Person)
Full-Time
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Job Description
AI Engineer
- Information Technology at Pond & Company AI Engineer
- Information Technology at Pond & Company in Peachtree Corners, Georgia Posted in 9 days ago.
Job Description:
AI Engineer- Enterprise Applications Position Overview Pond is seeking an AI Engineer to support the design and deployment of AI-enabled applications that enhance our technical and business operations.
Develop & Implement:
Build and maintain AI-enabled enterprise applications under the guidance of senior engineers and technical leadership.Integrate AI Services:
Implement integrations with large language model (LLM) APIs and related AI services within internal tools and workflows.Support RAG Systems:
Contribute to the development and optimization of retrieval-augmented generation (RAG) systems using structured and unstructured enterprise data.Translate Requirements:
Collaborate with cross-functional stakeholders to translate defined business and technical requirements into reliable AI-driven features and enhancements.Ensure Quality & Compliance:
Follow established governance, security, and performance standards to ensure AI implementations are reliable and compliant.Collaborate Cross-Functionally:
Work closely with software engineers, operational leaders, and AEC domain experts to support execution of Pond's enterprise AI initiatives. Required Qualifications- 3+ years of professional software engineering experience.
- Proficiency in Python and/or C#, with experience integrating APIs and external services.
- Hands-on experience working with LLM APIs or similar AI technologies in application development.
- Solid understanding of application architecture, system design principles, and secure development practices.
- Strong problem-solving skills and the ability to communicate technical concepts clearly to cross-functional stakeholders. Desired Additional Experience
- Experience within architecture, engineering, construction (AEC), or other technically complex industries.
- Exposure to RAG systems, vector databases, or multi-source enterprise data environments.
- Familiarity with enterprise data governance, security best practices, and compliance considerations related to AI solutions.
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