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.

Responsibilities

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

Requirements

Required Skills & Experience

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

Preferred Experience

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, LangSmith, 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

Development Environment

Self-hosted Linux platform with GPU acceleration for local model inference
Containerized services with shared internal networking
AI coding agents available and encouraged for day-to-day development
Local-first development with simple bypasses for auth and external dependencies
Focus on simplicity, observability, and reproducibility over framework sprawl

What We're Looking For

An applied AI engineer who ships — comfortable owning a feature from prompt design through production rollout
Someone who treats LLMs as one component in a system, not the whole system — strong fundamentals in APIs, data, and infrastructure
An engineer who is genuinely fluent with agentic coding tools and can demonstrate how they use them to multiply their output
A pragmatic builder who values evals, traces, and clear contracts over framework magic
A collaborator who can translate fuzzy stakeholder requests into concrete agent and application designs

Benefits

The base salary range for this position is $150,000-200,000 per year and reflects multiple levels within the role. Final level and compensation will be determined based on the candidate's skills, experience, qualifications, and internal equity.

In addition to a comprehensive package of health benefits that include company contributions, RAVE Aerospace offers a variety of additional benefits and perks to enhance your work-life balance experience including but not limited to:

A home allowance to elevate your home workspace
Discretionary bonus program
Future financial security with a 401(k) program with company match
Paid time off covering vacations, personal time off and sick days, capped off by an exciting year-end holiday shutdown
Embraced flexibility with our alternative work schedule (9/80) to navigate your workweeks with every other Friday off

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