Forward Deployed Software Engineer / AI Engineer

VDart Inc; Juno Beach (FL); On-site; USD 90,000 - 140,000; Full time

Job summary

Careers is seeking a Forward Deployed Software Engineer / AI Engineer to work directly with client engineering teams in enterprise environments. The role is hands-on and client-facing, deploying AI-powered developer tools, building custom integrations, and developing automation.

You will configure and troubleshoot tools like Devin, Windsurf, Claude Code, and GitHub Copilot; build MCP servers/clients; set up secure connections; and develop Python scripts to connect AI agents with enterprise

Qualifications

• 1-2 years of professional IT or software engineering experience.

Responsibilities

• Work onsite with client engineering teams to understand workflows, technical challenges, and integration requirements.

Skills

Local to Juno Beach, FL

1-2 years IT/Software engineering

Python

MCP architecture

AI coding assistants

ngrok/Cloudflare Tunnel/SSH tunneling

Devin Windsurf ClaudeCode GitHub Copil

Docker/CI/CD

prototyping / PoCs

Tools

Devin

Windsurf

Claude Code

GitHub Copilot

Job description

Forward Deployed Software Engineer / AI Engineer

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

Required Skills

• 1--2 years of professional IT or software engineering experience.
• Must be local to JunoBeach, FL, or willing to relocate at their own expense before the start date.
• Must be available to work onsite from Day1. No remote or hybrid option.
• Working knowledge of AI coding assistants such as Devin, Windsurf, ClaudeCode, GitHubCopilot, or similar tools.
• Understanding of MCP (ModelContextProtocol) architecture including experience building or consuming MCP servers.
• Hands‑on experience with ngrok, CloudflareTunnel, SSH port forwarding, or similar tunneling technologies.
• Strong Python skills for scripting, automation, and API integration.
• ExposuretoLLM fine‑; [some content truncated?

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.