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# AI/LLM Engineer

- **Company:** Gap Inc.
- **Location:** Springfield, PA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Frameworks, Microsoft Azure, Cloud Engineering, Github, Revision Control Systems, Integrated Development Environments, Python (Programming Language), Language Modeling, Performance Tuning, OpenAI, Tensorflow, Google Cloud, Pytorch, LangChain, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Build Management, Kubernetes, Information Technology, HuggingFace, Transformer Architectures, Machine Learning Operations, Claude
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-llm-engineer-springfield-pa--20308e6f-65bd-4c6c-a829-ee3697367d60

## About the Role

Artificial Intelligence (AI), Consulting, Business Processes, Problem Solving Skills, Artificial Intelligence (AI), Leading Edge Technology, Team Player, Research & Development (R&D), Modeling Languages, Operational Improvement, * Minimum Master's degree in Computer Science, Engineering, or a related technical field (PhD preferred); candidates with a Master's must have at least 2 years of relevant work experience since graduating.

 * Strong experience developing and deploying LLM-based applications, including fine-tuning and prompt engineering.
 * Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, along with version control tools like GitHub.
 * Familiarity with cloud-based AI services and APIs (e.g., OpenAI, AWS, Azure, GCP) and experience deploying models in scalable environments.
 * Solid understanding of NLP concepts, transformer architectures, and evaluation metrics for LLM systems.
 * Experience designing and implementing end-to-end training pipelines, including data shaping, model tuning, and performance optimization.
 * Ability to communicate complex technical concepts clearly across teams and to non-technical stakeholders.
 * Contributions to the AI/ML community through publications, open-source projects, or thought leadership., * People who thrive in a learning environment and enjoy learning, growing, and performing at their best; energized to continually push beyond their comfort zone.
 * Comfortable with ambiguity; eager to take on things they don't know how to do.
 * Curious and flexible when it comes to their own growth and development, as well as receptive to coaching and feedback to maximize their potential.
 * Willing to communicate and contribute thoughts, insights and new ideas to senior leaders both internally and externally.

## Description

You will be part of a tight knit, highly collaborative research and development team focused on building real-world AI applications. As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges.

You will work closely with teams to explore data, shape requirements, and integrate AI capabilities into internal tools and digital products. Your contributions will drive innovation and shape transformative projects across the organization., * Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges and improve operational efficiency.

 * Fine-tune foundation models and apply techniques such as retrieval-augmented generation (RAG) and prompt engineering.
 * Collaborate with cross-functional teams to integrate AI capabilities into internal tools, workflows, and digital products.
 * Evaluate and experiment with frameworks and tools like Hugging Face, LangChain, OpenAI, Claude, and LLaMA.
 * Build and deploy scalable LLM solutions across cloud-based and local environments, leveraging container orchestration tools where applicable.
 * Lead architectural decisions and guide implementation of reusable frameworks for model evaluation, optimization, and deployment.
 * Design, develop, and optimize autonomous AI agents.
 * Apply emerging research to practical use cases, staying current with advancements in NLP and generative AI.
 * Mentor team members and contribute to a collaborative, high-performance development environment.