Senior Staff AI Engineer, Agentic AI

Senior Staff AI Engineer, Agentic AI Location: Bay Area - Oakland, CA Employment Type: Full-time Experience: 8–15 years Focus: Agentic AI, Scientific Reasoning, AI Harnesses, Tool Use, Memory, Evaluation Systems About Our Client Our client is building the first AI-native operating system for materials science. Their platform helps scientists, chemists, and R&D teams reason through complex scientific problems using AI-native workflows, proprietary scientific data, and agentic systems designed for real-world research environments. The company is working with a uniquely valuable scientific data foundation, including trillions of proprietary scientific tokens that are not available anywhere else. This creates a rare opportunity to build AI systems that understand how scientists think, work, and make decisions. About the Role Our client is hiring a Senior Staff AI Engineer to own the technical direction of the agentic AI harness at the center of the platform. This is the most senior hands-on individual contributor role on the Agentic AI team. This person will define how the product evolves from a chat-based experience into an agentic-first platform where AI agents can reason, plan, use tools, remember context, evaluate outcomes, and operate across the full scientific workflow. This is a true 0-to-1 role. You’ll build the orchestration, tool use, memory, planning, and reasoning layer for production agent systems while helping lead two junior engineers on the AI harness. You’ll also partner closely with product and ML leadership to expand agent capabilities across every surface of the platform. What You’ll Do Own the technical direction for the agentic AI harnessBuild and expand production agent systems for scientific and chemistry workflowsDesign orchestration, tool use, memory, planning, and evaluation layers for agentic systemsHelp shift the platform from a chat-style interface into an agentic-first experienceBuild tools and sub-agent personas that reflect how chemists think and workIntegrate frontier reasoning models into the applicationExpand agent capabilities across scientific workflows and product surfacesContribute to potential fine-tuning programs for domain-specific scientific reasoningMake agent behavior observable, measurable, and reliable through tracing and evaluation systemsEvaluate agent performance against real scientific tasksDrive agent reliability to the level where customers can trust agents to act with increasing autonomyProvide technical leadership to junior engineers on the AI harness teamPartner closely with product, ML, and engineering leadership on roadmap and architecture What We’re Looking For 8–15 years of experience in AI engineering, software engineering, ML engineering, or related technical rolesStaff-level or Senior Staff-level experience setting technical direction, not just executing tasksExperience building sophisticated production agent systems from inception through scaleExperience building an agent harness or similar agentic infrastructureHands-on experience with low-level agentic frameworks such as LangGraph, LangChain, or equivalent toolsStrong full-stack programming experience across Python, React, TypeScript, or similar technologiesDeep understanding of LLMs, agent orchestration, tool use, memory, planning, evaluation, and production reliabilityAbility to design systems that move beyond chat into autonomous or semi-autonomous workflowsStrong judgment around system architecture, model behavior, observability, and product safetyExperience working in a startup, or a background combining big tech experience with startup executionAbility to lead technically while remaining deeply hands-on Technical Environment Relevant technologies and concepts include: PythonLangGraphLangChainAgentic frameworksFrontier LLMs, including GPT-4, Claude, and similar modelsBraintrustTracing and evaluation systemsRAGReactTypeScriptTool useMemory systemsAgent orchestrationScientific reasoning systems Preferred Background Our client is especially interested in candidates with: A degree in science, engineering, computer science, or a related technical fieldMaster’s or PhD from a strong technical universityScientific background or professional exposure to chemistry, physics, biology, materials science, or mechanical engineeringExperience fine-tuning reasoning modelsExperience building AI systems for scientific reasoningExperience working with proprietary datasets or domain-specific AI systemsExperience mentoring or leading junior engineers while staying hands-on Why This Opportunity Own the agentic AI layer at the center of an AI-native scientific platformBuild agent systems for real chemistry and materials science workflowsWork with proprietary scientific data that no one else has access toHelp define how scientists and AI reason togetherMove a platform from chat-based AI into agentic-first workflowsPartner directly with product and ML leadership on company-defining technical directionStep into a Senior Staff-level role with broad technical ownership and meaningful product influenceBuild at the intersection of frontier LLMs, agentic systems, scientific reasoning, and enterprise R&D Ideal Candidate Profile The ideal candidate is a Senior Staff-level AI engineer who has already built production agent systems and knows what it takes to move them beyond version one. They are deeply hands-on, technically opinionated, and capable of setting direction across agent orchestration, memory, tool use, evaluation, tracing, and product integration. They understand that reliable agent behavior requires more than model calls — it requires systems, feedback loops, observability, and strong product judgment. This person should be excited by the opportunity to build AI systems that help scientists reason, discover, and work in fundamentally new ways.