AI Engineer

Summary

Ruya AI is a venture-backed defense-tech company building AI-native intelligent software for sovereign institutions. They are seeking an AI Engineer to design and build multi-modal intelligence systems that convert complex operator requirements into secure and reliable AI capabilities.

Responsibilities

• Build asynchronous Python/TypeScript services with FastAPI, Pydantic, and asyncio
• Develop agent orchestration, subagent delegation, tool calling, and structured outputs
• Design MCP tools and AG-UI/SSE integrations
• Improve prompt, context, memory, and token-management strategies
• Build safeguards against prompt injection, data leakage, and unsafe tool use
• Create behavioral evals and regression datasets using Langfuse
• Trace model calls and tool execution with Langfuse, Sentry, and OpenTelemetry
• Diagnose failures spanning model behavior, tools, data sources, and distributed services

Skills

• Strong production Python and asynchronous programming experience
• Experience building LLM applications with tool use and multi-step reasoning
• Knowledge of structured output validation and non-deterministic system testing
• Practical understanding of prompt injection and sensitive-data risks
• Ability to evaluate AI behavior empirically rather than relying on demonstrations
• Experience with MCP, Langfuse, LiteLLM, Anthropic-compatible APIs, agent memory, CopilotKit, geospatial intelligence, or entity graphs
• Fine-tuning and pre-training of LLM models
• Post-training
• Agent and memory graph engineering
• RAG and knowledge systems

Qualifications

Must Haves

• Strong production Python and asynchronous programming experience
• Experience building LLM applications with tool use and multi-step reasoning
• Knowledge of structured output validation and non-deterministic system testing
• Practical understanding of prompt injection and sensitive-data risks
• Ability to evaluate AI behavior empirically rather than relying on demonstrations

Nice to Haves

• Experience with MCP, Langfuse, LiteLLM, Anthropic-compatible APIs, agent memory, CopilotKit, geospatial intelligence, or entity graphs
• Fine-tuning and pre-training of LLM models
• Post-training
• Agent and memory graph engineering
• RAG and knowledge systems

Benefits

• Employees (and their eligible dependents) can enroll in medical, dental, and vision insurance
• Commuter benefits
• Relocation assistance
• Paid time off built into the end of each year (subject to team and business needs) and based on location
• A supportive leave-of-absence program, including time off for military service and medical events