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AI Research Engineer Agentic AI

Job

Sunnyvale, CA

Sunnyvale, CA (In Person)

Full-Time

Posted 2 days ago (Updated 14 hours ago) • Actively hiring

Expires 7/10/2026

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Job Description

Your tasks
Responsibilities:
Design, build, and evaluate agentic AI systems that can plan, reason, act, and collaborate across tools and environments, including single- and multi-agent setups for complex, long-horizon tasks. Develop robust agent harnesses and evaluation frameworks covering end-to-end testing, regression analysis, trace logging, replayability, and metrics for success, cost, latency, robustness, and safety. Implement self-improving agent loops using reflection, critique, self-debugging, and iterative optimization strategies driven by agent experience, execution traces, and automated feedback. Architect and optimize agent memory systems, including short-term and long-term memory, retrieval-augmented generation, summarization, compression, forgetting policies, and privacy-aware retention. Enable reliable deployment of agents on constrained and edge environments, focusing on model/runtime optimization, partial or offline execution, secure tool-use, and seamless edge-cloud coordination. Your profile Basic Qualifications Bachelor or master's degree in computer science or engineering Strong software engineering skills in Python Hands-on experience with LLMs and agentic systems, such as tool-using agents, planner-executor patterns, multistep reasoning pipelines, RAG systems Solid understanding of ML fundamentals and practical model usage, including prompting, evaluation, and error analysis Ability to design experiments and interpret results, including ablations, statistical thinking, clear success criteria and measurable KPIs Strong communication and documentation skills including clear write-ups, reproducible experiments, and crisp technical presentations Preferred Qualifications 3+ years experiences in industrial research. Experience with one or more of the following topics: Agent frameworks Structured generation Agent memory management Self-improving agents LLM fine-tuning & reinforcement learning Model optimization for edge Harness engineering Hands-on experience on production of AI systems