AI Implementation Engineer / FDE

We are looking for a motivated Forward Deployed Engineer (FDE) / AI Engineer with 1–2 years of IT or software engineering experience to work directly with client engineering teams in an enterprise environment. This is a hands-on, client-facing role focused on deploying AI-powered developer tools, building custom integrations, developing automation, and troubleshooting technical solutions. The ideal candidate is technically curious, comfortable working in fast-paced environments, and passionate about emerging AI technologies and developer tooling.

Responsibilities

• Work onsite with client engineering teams to understand workflows, technical challenges, and integration requirements.
• Configure, deploy, customize, and troubleshoot AI coding tools such as Devin, Windsurf, Claude Code, and GitHub Copilot.
• Build and configure Model Context Protocol (MCP) servers and clients to connect AI agents with internal tools, APIs, and databases.
• Set up secure connectivity using ngrok, Cloudflare Tunnel, SSH tunneling, and similar technologies.
• Develop Python scripts, automation, and API integrations to connect AI agents with enterprise systems.
• Assist with LLM adaptation and fine-tuning activities, including LoRA, PEFT, prompt tuning, dataset preparation, and model evaluation.
• Rapidly develop prototypes and proof-of-concepts based on client requirements and feedback.
• Troubleshoot and debug integrations in live client environments.
• Create technical documentation and provide technical enablement and training to client teams.
• Gather client feedback and communicate technical requirements and challenges to product and engineering teams.

Requirements

• 1–2 years of professional IT or software engineering experience.
• Must be local to Juno Beach, FL, or willing to relocate at their own expense before the start date.
• Must be available to work onsite from Day 1. No remote or hybrid option.
• Working knowledge of AI coding assistants such as Devin, Windsurf, Claude Code, GitHub Copilot, or similar tools.
• Understanding of MCP (Model Context Protocol) architecture, including experience building or consuming MCP servers.
• Hands-on experience with ngrok, Cloudflare Tunnel, SSH port forwarding, or similar tunneling technologies.
• Strong Python skills for scripting, automation, and API integration.
• Exposure to LLM fine-tuning, including LoRA/PEFT, dataset preparation, and model evaluation.
• Familiarity with Git/GitHub and standard version-control practices.
• Basic understanding of REST APIs, webhooks, and cloud platforms such as AWS, Azure, or Google Cloud Platform.

Preferred Skills

• Experience with Docker, containerization, and CI/CD pipelines.
• Exposure to vector databases and RAG (Retrieval-Augmented Generation).
• Prior client-facing, consulting, or technical support experience.
• Familiarity with prompt engineering and agentic AI workflows.
• Experience rapidly developing technical prototypes and proof-of-concepts.

Key Soft Skills

• Strong communication and interpersonal skills.
• Comfortable working directly with clients and technical stakeholders.
• Ability to work independently in ambiguous and fast-paced environments.
• Strong troubleshooting and problem-solving abilities.
• Comfortable debugging live technical issues under pressure.
• Strong curiosity and willingness to learn emerging AI technologies.
• Creative and solution-oriented mindset.