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.

Required Skills & Experience

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).

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