Agentic AI Software Developer

Job DescriptionResponsibilities: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.QualificationsBasic QualificationsBachelor or master's degree in computer science or engineeringStrong software engineering skills in PythonHands-on experience with LLMs and agentic systems, such as tool-using agents, planner-executor patterns, multistep reasoning pipelines, RAG systemsSolid understanding of ML fundamentals and practical model usage, including prompting, evaluation, and error analysisAbility to design experiments and interpret results, including ablations, statistical thinking, clear success criteria and measurable KPIsStrong communication and documentation skills including clear write-ups, reproducible experiments, and crisp technical presentationsPreferred Qualifications3+ years experiences in industrial research.Experience with one or more of the following topics:Agent frameworksStructured generationAgent memory managementSelf-improving agentsLLM fine-tuning & reinforcement learningModel optimization for edge