Software Engineer, Instabase

• 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

Desirable

• SuperApp is our flagship AI agent workspace. It unifies communication, collaboration, file sharing, and multimodal reasoning into a single, seamless platform
• Powering SuperApp is our Agent Harness—the underlying execution engine that manages agent states, orchestrates multi-turn planning and tool execution, enforces strict security guardrails, and runs untrusted, dynamic code in secure, sandboxed environments
• As a Staff AI Engineer on the Agent Harness team, you will design the foundation of this runtime execution environment, enabling SuperApp to act as a resilient, highly scalable, and ultra-secure agentic operating system for the enterprise
• 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
• 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