> Markdown version of [/jobs/ext/2593514-forward-deployed-engineers](https://www.wearedevelopers.com/jobs/ext/2593514-forward-deployed-engineers). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineers - **Company:** VDart, Inc. - **Location:** Juno Beach, FL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Encodings, Databases, Software Debugging, Programming Tools, Python (Programming Language), Performance Tuning, Rapid Prototyping Process, Software Engineering, Solution Deployment Descriptor, Scripting, Cloud Platform System, GitHub Copilot, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Containerization, Information Technology, Cloudflare, Restful APIs, Webhooks, Software Version Control, Docker - **Published:** August 10, 2026 - **Apply:** https://www.careerjet.com/jobad/us8f5d85cbac0e11c75b94a21d38843e43 ## About the Role * 1 2 years of professional IT/software engineering experience. * Must be local to Juno Beach, FL or willing to relocate at own expense before start date - no remote work, no relocation assistance implied unless stated otherwise. * Available to start onsite from Day 1 - no phased/remote ramp-up. * Working knowledge of AI coding assistants: Devin, Windsurf, Claude Code, GitHub Copilot, or similar. * Understanding of MCP (Model Context Protocol) architecture - building or consuming MCP servers. * Practical experience with tunnelling tools (ngrok, Cloudflare Tunnel, SSH port-forwarding, or similar). * Proficient in Python - scripting, automation, API integration. * Exposure to LLM fine-tuning techniques (LoRA/PEFT, dataset preparation, evaluation). * Familiarity with Git/GitHub workflows and version control. * Basic understanding of REST APIs, webhooks, and cloud environments (AWS/Azure/GCP). Preferred / Nice-to-Have * Experience with containerization (Docker) and CI/CD pipelines. * Exposure to vector databases and RAG (Retrieval-Augmented Generation) pipelines. * Prior client-facing or consulting experience. * Familiarity with prompt engineering and agentic workflows. Soft Skills * Strong communication skills for direct client interaction. * Comfortable working independently in ambiguous, fast-paced environments. * Problem-solver mindset - able to debug live issues under client pressure. * Curious to learn new things and exhibit fresh ideas - stays current with fast-evolving AI tooling and brings innovative approaches to client problems. ## Description We are looking for a Forward Deployed Engineer (FDE) with 1 2 years of IT experience to work directly with clients, embedding AI-powered developer tools and custom solutions into their existing workflows. This is a hands-on, client-facing technical role blending software engineering, AI tooling expertise, and rapid solution deployment. Key Responsibilities * Client Embedding: Work onsite with client engineering teams in Juno Beach to understand workflows, pain points, and integration requirements. * AI Coding Tool Deployment: Configure, customize, and troubleshoot AI development tools such as Devin, Windsurf, Claude Code, and GitHub Copilot within client environments. * MCP Integration: Build and configure Model Context Protocol (MCP) servers/clients to connect AI agents with internal tools, databases, and APIs. * Secure Connectivity: Set up and manage tunnelling solutions (e.g., ngrok, Cloudflare Tunnel, SSH tunnels) to enable secure access between client infrastructure and external tools/agents. * Custom Tooling: Write Python scripts, automation, and glue code to bridge AI agents with client-specific systems. * LLM Fine-Tuning: Assist in fine-tuning or adapting LLMs (e.g., LoRA, PEFT, prompt-tuning) to improve performance on client-specific tasks and datasets. * Rapid Prototyping: Quickly build proof-of-concepts and iterate based on direct client feedback. * Documentation & Enablement: Document integrations and train client teams on effective use of deployed AI tools. * Feedback Loop: Relay client requirements and friction points back to the product/engineering team to influence roadmap. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Beyond Webhooks: The Future of Scalable API Event Delivery](https://www.wearedevelopers.com/videos/100312-beyond-webhooks-the-future-of-scalable-api-event-delivery) - [JavaScript? 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