AI Engineer

About Instabase & SuperApp

Instabase is on a mission to democratize access to cutting-edge AI innovation, enabling organizations to solve previously unsolvable unstructured data problems.

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.

Role Overview

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.

About You

• Experience: Minimum 8+ 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.

Compensation: The base salary range for this role is $230,00 to $315,000 + bonus, equity, and benefits. The actual pay may vary based on factors such as location, experience, and skills.