Hiring: Software Engineer - Agent Harness Company: Instabase Location: San Francisco, CA Job Posted Time: 2026-09-10 10:59:36 Target Skills & Keywords : API Design, Docker, Kafka, Kubernetes, LLM, LangChain, Microservices, Python, RabbitMQ, React, Redis, Systems Engineering, TypeScript, gRPC About the job Experience: •6+ years of professional software engineering experience, with a proven track record of designing, scaling, and operating mission-critical distributed systems. •2+ years of production experience building or modifying agent execution environments, LLM orchestrators, or tool-calling frameworks (e.g., custom runtimes, LangChain, AutoGen, or similar systems). Required Skills: •We are seeking a visionary systems-minded AI engineer to lead the design, architecture, and development of the . In this role, you will bridge the gap between advanced foundation models (LLMs) and reliable, production-grade execution. •Harness Architecture & State Management: Architect the next-generation execution runtime (Agent Harness) that drives SuperApp’s planning, reasoning, memory retention, and tool-execution loops. Build reliable state machines capable of pausing, resuming, and versioning agent trajectories. •Secure Sandbox Execution: Design and scale highly secure, isolated, and ephemeral environments (using Docker, gVisor, WebAssembly, or microVMs) to execute agent-generated code safely without putting host infrastructure at risk. •Tool & Integration Frameworks: Build and maintain high-throughput APIs and integration layers (such as the Model Context Protocol - MCP) that connect SuperApp to external services, databases, web search utilities, and complex file processors. •Security & Guardrail Engineering: Engineer robust system-level guardrails to detect and mitigate prompt injection, defend against jailbreak attempts, and ensure strict compliance with system prompt instructions and data isolation boundaries. •Performance & Context Optimization: Implement advanced routing, context window pruning, and context caching strategies to optimize LLM token usage, minimize round-trip latencies, and drastically reduce the operational cost of complex agent loops. •Technical Strategy & Mentorship: Write comprehensive high-level design documents, align cross-functional engineering teams on the technical roadmap, and mentor senior and mid-level software engineers across the organization. Qualifications: •Agentic AI Expertise: 2+ years of production experience building or modifying agent execution environments, LLM orchestrators, or tool-calling frameworks (e.g., custom runtimes, LangChain, AutoGen, or similar systems). •Backend Mastery: Expert proficiency in Go and Python. You have a pragmatic, deep understanding of concurrent programming, microservices, gRPC, and highly scalable API design. •Runtime Isolation & Security: Strong experience with containerization and virtualization technologies (Docker, Kubernetes) and a solid grasp of sandboxing untrusted code execution. •Distributed Systems Fundamentals: Deep familiarity with message brokers (e.g., Kafka, RabbitMQ), caching infrastructure (Redis), and relational/non-relational database design. •Prior experience developing developer tools, SDKs, or extensible plug-in architectures. Compensation: •: The base salary range for this role is $230,00 to $315,000 + bonus, equity, and benefits Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!