Senior AI Engineer

Airo Digital Labs, LLC; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Airo Digital Labs, LLC is seeking a seasoned ML/AI engineer to design and build the Signal Engine, Action Engine, Librarian Agent and Ontology Graph, turning signals into coordinated, agent-driven actions in production.

Required: 5+ years in ML/AI engineering with production LLM or agent systems, strong Python, and experience with LangGraph/LangChain and Azure AI Foundry. Knowledge of graph databases and vector retrieval is a plus.

Qualifications

• 5+ years in ML/AI engineering, including production LLM or agent systems.
• Experience taking an agentic or RAG system from prototype to reliable, monitored production.
• Strong Python and production ML/AI engineering skills.
• Experience with LangGraph, LangChain, or similar LLM orchestration patterns.
• Familiarity with Azure AI Foundry or equivalent model deployment.

Responsibilities

• Design and implement agentic workflows with LangGraph and Azure AI Foundry that power the Signal and Action Engines.
• Build the Librarian Agent — retrieval-augmented reasoning over the Ontology Graph and Graph Database.
• Model and evolve the Ontology Graph; implement graph and vector retrieval strategies.
• Integrate agents with tools and other services via MCP / A2A and webhooks.
• Establish evaluation, guardrails, observability and cost controls for LLM/agent behavior in production.
• Partner with the Data Engineer on the data and features that feed the intelligence layer.
• Nice to have: Ontology/knowledge-graph modelling; MCP/A2A protocol experience; MLOps/LLMOps.

Skills

Python

Production ML/AI engineering

LLM orchestration

Prompt engineering

Agentic frameworks

RAG / vector search

LangGraph / LangChain

Azure AI Foundry

Tools

Neo4j

Cosmos DB (Gremlin)

Graph databases

Embeddings

Job description

The technical owner of the Core Intelligence layer — the platform’s differentiator. You design and build the Signal Engine, Action Engine, Librarian Agent and Ontology Graph, turning signals into coordinated, agent-driven action.

Key Responsibilities

• Design and implement agentic workflows with LangGraph and Azure AI Foundry that power the Signal and Action Engines.
• Build the Librarian Agent — retrieval-augmented reasoning over the Ontology Graph and Graph Database.
• Model and evolve the Ontology Graph; implement graph and vector retrieval strategies.
• Integrate agents with tools and other services via MCP / A2A and webhooks.
• Establish evaluation, guardrails, observability and cost controls for LLM/agent behavior in production.
• Partner with the Data Engineer on the data and features that feed the intelligence layer.

Must-have Skills & Technologies

• Strong Python and production ML/AI engineering.
• Agentic frameworks — LangGraph (or LangChain, LlamaIndex, Semantic Kernel) — and LLM orchestration patterns.
• Azure AI Foundry or equivalent (Azure OpenAI, Bedrock, Vertex) model deployment and management.
• RAG, embeddings, vector search, and graph-based retrieval; hands-on with a Graph Database (Neo4j, Cosmos DB Gremlin or similar).
• Prompt engineering, structured output / tool-calling, and LLM evaluation frameworks.

Prior Experience

• 5+ years in ML/AI engineering, including production LLM or agent systems (not only notebooks/POCs).
• Experience taking an agentic or RAG system from prototype to reliable, monitored production.

Nice to Have

• Ontology / knowledge-graph modelling; MCP / A2A protocol experience.
• MLOps / LLMOps: eval harnesses, prompt versioning, drift and cost monitoring.