Job Title Staff Software Engineer - Agentic AI Systems About the Role We are seeking a Staff Agentic AI Engineer to lead the architecture, implementation, and production deployment of advanced agentic AI systems. In this role, you will serve as a technical authority for multi‑agent systems across Cognichip, driving long‑horizon autonomous workflows that integrate proprietary models, semiconductor design tools, and cloud infrastructure. You will design systems that reason across multiple steps, manage memory and knowledge grounding, and operate reliably in production over extended periods. This is a senior individual contributor leadership role. You will define architectural patterns, raise engineering standards, mentor other engineers, and partner closely with Applied AI, Product Engineering, and Platform teams to translate cutting‑edge research into scalable enterprise solutions. Success in this role is measured not by prototypes, but by robust, production‑grade agentic systems shipped to customers. Key Responsibilities Technical Leadership & Architecture Own the end‑to‑end architecture of agentic AI workflows, including reasoning pipelines, memory systems, RAG, evaluation frameworks, and orchestration patterns. Define best practices for supervisor/sub‑agent coordination, fault tolerance, long‑horizon reasoning, and system robustness. Serve as Cognichip’s internal expert on agentic AI system design and production deployment. Build & Operate Agentic Systems Design and implement multi‑step autonomous agents with advanced memory, Retrieval‑Augmented Generation (RAG), and integrations to tools, APIs, and enterprise data sources. Deliver production‑grade workflows deployed on cloud platforms (AWS preferred), with strong observability, monitoring, and reliability guarantees. Drive continuous improvement of agent quality, cost efficiency, and performance in real customer environments. Evaluation & Optimization Define and implement comprehensive evaluation pipelines for agentic systems: Task success / failure classification Grounding accuracy Reasoning robustness Tool‑use reliability Long‑horizon completion rates Establish regression testing and benchmarking strategies using frameworks such as LangSmith or custom evaluation infrastructure. Balance automated evaluation with human‑in‑the‑loop feedback for complex workflows. Cross‑Functional Collaboration Partner with Applied AI researchers to productionize new capabilities. Work with backend/platform engineers to integrate agents with cloud infrastructure and enterprise systems. Collaborate with product managers to translate semiconductor workflows into agent‑driven user experiences. Organizational Impact Set technical direction for agentic AI systems across teams. Mentor senior and mid‑level engineers. Raise engineering standards around agent architecture, evaluation, and production readiness. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field. 8–12+ years of professional software engineering experience. 3+ years building and deploying production‑grade agentic AI systems. Deep hands‑on experience with: Multi‑agent orchestration frameworks (LangGraph, LangChain, LangSmith, or equivalents) RAG pipelines and memory systems Agent evaluation methodologies Strong proficiency in Python and backend cloud services (AWS preferred). Proven track record delivering complex AI systems into production. Preferred Qualifications Contributions to open‑source AI projects or frameworks. Experience with multi‑agent orchestration patterns at scale. Knowledge of reinforcement learning, planning algorithms, or autonomous reasoning. Track record of deploying agentic AI systems in production at scale. What We Offer The chance to work on state‑of‑the‑art AI systems that push the boundaries of autonomy and reasoning. A collaborative environment where engineering meets research. Competitive compensation and equity in a fast‑growing AI startup. A culture that values ownership, curiosity, and technical excellence. #J-18808-Ljbffr