Forward Deployed Engineer (AI-Augmented Integration)

About the Role This is not a traditional, desk-bound software engineering role. We are looking for a highly autonomous Forward Deployed Engineer (FDE) to act as the technical bridge between our core AI products and our enterprise clients. You will be deployed directly to client sites globally to integrate our AI systems and necessary edge point into their existing, often legacy, local network infrastructures.

We do not care what programming languages you have memorized. We care about your ability to act as an orchestrator of code—using AI tools to rapidly generate, test, and deploy functional logic across any environment. You must possess the architectural understanding to define the problem, the "vibe coding" skills to accelerate the solution, and the extreme ownership to see it running reliably in production.

Core Responsibilities:

• Intent-Driven Development ("Vibe Coding"): Leverage AI coding agents (e.g., Cursor, GitHub Copilot, Claude) to rapidly generate boilerplate, write functional logic, and build API connectors. You will operate as a polyglot, adapting instantly to whatever language or framework the client's legacy environment demands.
• On-Site Systems Integration: Manage the physical and digital deployment of AI hardware and software systems at enterprise client sites. Map local networks, establish secure connections, and force disparate systems to communicate.
• Autonomous Problem Discovery & Resolution: Do not wait for perfectly scoped Jira tickets. You will proactively interrogate client systems, identify latency, failure points, or network blockers, and independently architect and deploy the fix on the spot.
• AI Debugging & Hallucination Management: AI generates the code, but you own the deployment. You must possess the deep systems knowledge required to instantly spot AI hallucinations, security flaws, or inefficient logic in the generated output before it impacts a live client environment.
• Overseas Deployment & Client Management: Travel internationally a minimum of 30% of the time. You must navigate undocumented local networks and communicate technical realities directly to regional stakeholders without escalating every issue back to headquarters.

Education, Age & Pedigree

• Zero Traditional Requirements: We do not filter by university degree, GPA, age, or standard corporate pedigree. We care strictly about your output, your logic, and your ability to execute under pressure.
• Unconventional Backgrounds Welcome: You do not need a traditional computer science resume. If you are self-taught, transitioned from a completely different industry, or simply learned to build and integrate complex systems autonomously using AI, you are eligible to apply—provided you can pass the technical integration assessment.

Disqualifiers (Who Should Not Apply)

• Traditionalists: Engineers who revert to writing everything manually because it feels "safer" or "more comfortable." If your instinct is to spend days writing what an LLM could structure in hours, you will fail here.
• Order-Takers: Individuals who require detailed spec documents, pristine development environments, and constant direction from a product manager to begin engineering.
• Syntax Purists: Developers who care more about specific programming language paradigms than shipping integrated, working solutions to the client under a tight deadline.

Required Baseline Competencies

• Advanced Context Management: Demonstrated ability to provide LLMs with the precise context, system constraints, and architectural guidelines required to generate production-ready code.
• Systems Architecture & Networking: A functional understanding of how complex, distributed systems interact (APIs, databases, local networks, cloud infrastructure, and hardware integration). You must understand the system well enough to tell the AI exactly what to build.
• High Tolerance for Ambiguity: The ability to walk into a messy, unstructured client environment, systematically map it, and deploy an integration seamlessly.