AGENTC DeveloperOptimal Inc. • Warren, MI, US
AGENTC Developer
Optimal Inc. • Warren, MI, US
[job_card.1_day_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]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. 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
Job Description
Job Description
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
Education
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