Job Title: Agentic AI EngineerWe are seeking a highly skilled Agentic AI Engineer to support advanced R&D initiatives focused on next-generation AI agents and conversational intelligence systems. This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks.
The ideal candidate brings a strong blend of machine learning expertise, systems thinking, and hands-on experience with agent-based architectures, and thrives in a fast-paced, research-driven environment.
Key Responsibilities
- Design and develop agentic AI systems using GPT-style and other large language model architectures
- Architect and optimize agent memory systems, including short-term, long-term, and retrieval-based memory
- Implement multi-step reasoning, planning, and chain-of-thought pipelines for complex problem solving
- Build scalable context management frameworks to support dynamic, multi-turn conversations
- Develop text-to-structured-data pipelines for automated knowledge extraction and workflow automation
- Collaborate with cross-functional R&D teams to integrate agent-based solutions into innovative products and research initiatives
- Evaluate model performance and continuously improve accuracy, efficiency, and reasoning capabilities
- Document system designs, experiments, and technical findings
Required Qualifications
- 3-5 years of industry experience in AI/ML, LLM development, or agent-based systems
- Strong hands-on experience with large language models (prompt engineering, fine-tuning, evaluation)
- Experience building or working with agent frameworks, memory systems, or planning/reasoning architectures
- Solid understanding of context handling, retrieval-augmented generation (RAG), and optimization techniques
- Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow)
- Experience with tools and ecosystems such as vector databases, APIs, and distributed systems is a plus
- Strong problem-solving skills and ability to work in research-oriented, collaborative environments
Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- Experience contributing to research publications, open-source projects, or experimental AI platforms
