Key Responsibilities
Design and implement agentic AI workflows, including planning, reasoning, tool usage, and memory management
Assist in building multiagent systems and agent orchestration flows
Prototype agent pipelines using LLMs and prompt engineering techniques
Evaluate agent behavior, performance, reliability, and failure modes
Contribute to system documentation, design notes, and technical reports
Collaborate with engineers to improve system robustness, scalability, and observability
Required Qualifications
Currently pursuing a Master’s, or PhD in:
Computer Science
Artificial Intelligence
Strong programming skills in Python
Understanding of:
Basic ML and deep learning concepts
Natural Language Processing (NLP)
Familiarity with:
Preferred Qualifications (Nice to Have)
Experience with:
Agent frameworks (e.g., LangChain)
Workflow orchestration or state machines
Knowledge of:
Reinforcement learning basics
LLM fine-tuning
Vector and graph databases
Prior internship or project experience in AI/ML systems
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