Warren, MI, US
AGENTC Developer
Position Overview
Seeking a highly skilled AGENTC Developer to support advanced research efforts in AI agent systems and next-generation conversational intelligence. The ideal candidate will have deep technical expertise
in large-language-model (LLM) development, context and memory architectures, and advanced reasoning frameworks. This role will focus on designing, implementing, and optimizing AGENTC capabilities for internal R&D applications.
Key Responsibilities
- Develop and refine AGENTC-based systems leveraging GPT-style architectures and advanced LLM techniques.
- Implement and optimize short-term memory management modules within conversational agents.
- Design, test, and improve chain-of-reasoning and multi-step inference pipelines.
- Build and manage context-handling frameworks to maintain robust agent performance across dynamic conversational environments.
- Develop tools and pipelines for text-to-structured-database conversion, enabling automated knowledge capture and retrieval.
- Collaborate with R&D engineers and researchers to integrate agent technologies into broader GM innovation initiatives.
- Document architectures, algorithms, and experimental results for research and internal decision-making.
Required Skills & Experience
- Strong proficiency with GPT-based or similar LLM frameworks (training, fine-tuning, evaluation, prompt engineering).
- Experience designing or implementing agent memory architectures (short-term, long-term, retrieval-augmented systems).
- Hands-on experience with chain-of-thought, reasoning models, or planning-based agent systems.
- Expertise in context management techniques, including context compression, retrieval optimization, and dynamic context shaping.
- Proficiency in text processing, knowledge extraction, and conversion of unstructured text to structured databases.
- Strong programming skills (Python preferred) and familiarity with modern AI/ML tooling and frameworks.
- Demonstrated ability to work in highly collaborative, research-oriented environments.
Education
- Ph.D. in Computer Science, AI, Machine Learning, Computational Linguistics, or a related field preferred
- Master's degree considered with exceptional experience in LLM or agent systems development
