About the Company
This company is building AI systems that sit directly in the flow of real commercial and operational decision making. This is not a research role and not prompt tinkering. You will be designing, building, and deploying AI systems that automate and augment complex workflows in production environments.
Responsibilities
- Build and deploy production-grade AI systems, primarily around LLMs and agentic workflows
- Design and implement RAG pipelines over structured and unstructured enterprise data
- Build multi-step, tool-using agents that interact with internal systems and APIs
- Own evaluation, monitoring, and iteration of models in live environments
- Work hands-on across the stack, from data ingestion through to application logic
- Contribute to architectural decisions as the AI platform scales
Requirements
- Strong Python experience in production settings
- Hands-on experience with LLMs beyond basic prompting
- Solid understanding of RAG, embeddings, vector databases, and retrieval strategies
- Experience with frameworks such as LangChain, LangGraph, or equivalent
- Comfortable working with messy data and evolving requirements
- Clear thinker who can communicate trade-offs and move quickly without cutting corners
Nice to Have
- Experience with agent orchestration and tool calling
- Exposure to industrial, manufacturing, or complex B2B domains
- Experience deploying AI systems to cloud infrastructure
- Familiarity with LLM observability and evaluation tooling