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# Software Engineer - Agent Harness

- **Company:** Superapp, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $315,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Databases, Concurrent Computing, Software Debugging, Programming Tools, Distributed Systems, Middleware, Python (Programming Language), Message Broker, RabbitMQ, Redis, Software Engineering, TypeScript, Management of Software Versions, Virtualization Technology, ReactJS, Large Language Models, State Machines, Caching, Backend, Agentic-AI, Containerization, Kubernetes, Information Technology, AutoGen, Integration Frameworks, Apache Kafka, Non-relational Database, Search Engines, Front End Software Development, Api Design, Model Context Protocol, Grpc, Docker, Microservices
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_6e006f4f461319299279273ea05f3fb8

## About the Role

* Experience: Minimum 6+ years of professional software engineering experience, with a proven track record of designing, scaling, and operating mission-critical distributed systems.
 * 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.
 * Education: Bachelor's or Master's degree in Computer Science, engineering, or equivalent practical systems engineering experience.

Nice to Have (Preferred)

 * Prior experience developing developer tools, SDKs, or extensible plug-in architectures.
 * Experience with frontend integration (React, TypeScript) to support human-in-the-loop debugging interfaces or agent visual builders.
 * Experience working in high-growth, fast-paced startup environments.

## Description

We are seeking a visionary systems-minded AI engineer to lead the design, architecture, and development of the Agent Harness. In this role, you will bridge the gap between advanced foundation models (LLMs) and reliable, production-grade execution.

You will not just be "vibe coding" prompts ; you will build the actual state machine, execution sandbox, tool-calling middleware, and security containment layers that allow AI agents to safely execute code, search the web, manipulate files, and query databases in real-time. This is a high-leverage role requiring deep expertise in distributed backend systems, runtime isolation, and stateful agent choreography.

What You'll Do (Responsibilities)

 * 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.