Senior AI Engineer (Generative AI / LLM Systems)

About the Position

Senior AI Engineer (Generative AI / LLM Systems)

Cerebre builds software that helps industrial companies understand and operate complex facilities. Our platform transforms engineering diagrams, operational data, and documentation into an ontology-driven knowledge graph, PlantGraph, that models equipment, instrumentation, flow, and process relationships across a facility.

This foundation enables engineers and operators to reason about industrial systems with greater clarity and speed. We are now integrating advanced AI capabilities directly into this platform, enabling natural language interaction with facility data, graph-aware reasoning over engineering systems, and AI-driven workflows that operate across diagrams, documentation, and operational processes.

Responsibilities

• Build AI Systems That Reason Over Structured Industrial Data
  • Design systems that allow LLMs to interpret and reason over PlantGraph and its underlying ontology, combining graph queries, ontology structures, and engineering data into reliable, explainable outputs.
• Create Natural Language Interfaces Over Complex Systems
  • Build chat-based experiences that allow users to explore facility systems, navigate diagrams, and query equipment and process relationships through conversation.
• Orchestrate AI Across Graphs, Documents, and Workflows
  • Develop systems that combine:
    • Enable AI Agents to Safely Interact with the Platform
      • Design APIs and tools that allow AI agents to operate on PlantGraph and system capabilities, ensuring interactions are observable, reliable, and production-safe.
    • Productionize AI Systems at Scale
      • Turn prototypes into production systems.
    • Own Ambiguous, High-Impact Problems
      • Work across engineering, ML, and domain teams to define and solve complex problems, including identifying and addressing gaps in data, ontology, and system design.

Requirements

• Required Qualifications

  • 5+ years in software engineering, ML engineering, or applied AI
  • Experience building AI systems that combine structured data with LLMs
  • Strong experience with RAG, embeddings, and retrieval systems
  • Experience building production AI systems (not just prototypes)
  • Strong Python and backend engineering experience
  • Experience designing scalable APIs and services
  • Ability to take ownership of complex, ambiguous problems

• Preferred Qualifications

  • Experience with LLM agents or tool-based AI systems that interact with external systems via APIs or structured tools, including familiarity with emerging standards such as MCP
  • Knowledge graph or graph database experience
  • Exposure to industrial systems, P&IDs, or engineering workflows
  • Experience with PyTorch / TensorFlow
  • Distributed systems / cloud infrastructure experience

Tech Stack

• LLMs: OpenAI, open-source models (Hugging Face)
• AI Frameworks: LangChain, LlamaIndex, MCP
• ML: PyTorch, TensorFlow
• Data: Vector DBs, FalkorDB (graph), hybrid retrieval systems supporting PlantGraph and structured reasoning over engineering data
• Backend: Python services & APIs
• Frontend:.NET-based applications

We Offer

• Remote Work: Fully remote position
• Impactful Work: Build AI systems that reason over structured engineering systems, integrate deeply into workflows, and must be correct, explainable, and production-ready

About the Company

We are cross-functional collaborators.

We blend manufacturing process knowledge with software and big data engineering expertise to create value in physical settings.

We are experienced.

We are armed with industry-leading experts in numerical simulation, combustion, power, computational fluid dynamics, and chemical process modeling.

We are serious builders.

We develop our platforms using leading practices in IT/OT architecture, OT security, AI architecture, ML Ops, and Platform engineering.