AI Developer

RAVE Aerospace is redefining the in‑flight experience through innovative entertainment and connectivity solutions trusted by airlines around the world. We combine advanced hardware, intelligent software, and connected digital platforms to help airlines create more engaging, seamless, and reliable passenger experiences. As the future of air travel evolves, RAVE is building the technology that keeps passengers connected from takeoff to landing.

We are seeking an experienced AI Developer to design, build, and scale production AI applications and autonomous agents on a modern, self‑hosted platform. This role will play a key part in shaping the architecture, tooling, and engineering standards that power AI capabilities across the organization. Working across the full technology stack, the AI Developer will leverage large language models and AI coding agents as core components of the development process to deliver reliable, high‑impact solutions.

This is a highly influential, hands‑on engineering role focused on building practical, production‑ready AI systems in a fast‑moving and collaborative environment.

This individual is equally comfortable discussing architecture and implementing solutions, with a strong sense of ownership and a desire to influence platform direction, tooling decisions, and engineering best practices. They are curious, adaptable, and energized by solving complex problems while building scalable, maintainable systems. Strong collaboration and communication skills are essential, as this role partners closely with technical and cross‑functional teams to bring AI capabilities into production.

• Design and implement AI‑powered services, agents, and internal applications
• Build and maintain MCP (Model Context Protocol) servers that expose enterprise systems to LLM clients
• Develop end‑to‑end features — backend services, data pipelines, and user‑facing UIs — using agent‑assisted workflows
• Design retrieval pipelines (chunking, embeddings, vector search) and prompt strategies
• Integrate LLMs across managed and self‑hosted runtimes, choosing the right tool for cost, latency, and privacy constraints
• Instrument prompts and agents with traces, evals, and regression checks
• Enforce shared platform conventions: authentication, RBAC, container networking, secrets handling
• Mentor other engineers on applied AI patterns and on getting the most out of agentic coding tools

• 10+ years of experience in software engineering
• 2+ years working directly with AI/ML or LLM‑based applications
• Strong software engineering fundamentals) — systems thinking, debugging, API design, data modeling
• Production experience shipping web services and/or data products in any modern stack
• Demonstrated fluency with AI coding agents (Claude Code, Cursor, Copilot, Aider, or similar) as part of daily work
• Practical experience integrating LLMs into real products (any major provider)
• Working knowledge of retrieval‑augmented generation (RAG): embeddings, vector search, chunking strategies
• Solid SQL and relational data modeling skills
• Comfortable with containerized development (Docker / docker‑compose)
• A pragmatic approach to tests, observability, and operational quality

Hands‑on experience with any of the following:

• Model Context Protocol (MCP) — building servers and/or clients
• Managed LLM platforms (Bedrock, Anthropic, OpenAI, Azure OpenAI)
• Self‑hosted LLM runtimes (Ollama,vLLM, llama.cpp)
• Production vector databases (Qdrant,pgvector,Weaviate, Pinecone)
• LLM observability and eval tooling (Langfuse,Lang Smith, Phoenix, etc.)
• Workflow orchestration (Prefect, Airflow,Dagster)
• Modern frontend work (React or similar) for building internal tools and agent UIs
• SSO / OIDC and role‑based access control patterns
• Prompt engineering and structured‑output techniques (tool use, JSON schema, function calling)
• Experience operating GPU workloads on Linux
• Prior technical leadership or tech‑lead experience on AI / data products

• Self‑hosted Linux platform with GPU acceleration for local model inference
• Containerized services with shared internal networking
• AI coding agents available and encouraged…