5 of 5 LangChain Jobs in Northern Ireland

models, or LLM-based analytics. Strong proficiency in Python (preferred) and/or JavaScript/TypeScript. Hands-on experience with AI frameworks (TensorFlow, PyTorch, LangChain) and LLM APIs (Azure OpenAI, OpenAI API, Anthropic, AWS Bedrock). Experience with Microsoft Bot Framework, Dialogflow, or similar conversational-AI platforms. Deep understanding ...

agents with enterprise systems, APIs, and data sources for autoremediation. Develop scalable, reliable, and secure AI agent architectures. Stay current with GenAI agent frameworks (LangChain, LlamaIndex, Autogen) and IT automation trends. Build intuitive frontends (Next.js, React, TypeScript) and backend services (Python). Provide technical guidance on agentic AI principles ...

Engineering roles, preferably building with LLMs and/or Agentic Systems, from development to production. Hands-on experience with LLM frameworks (e.g. langchain, langgraph, llamaindex, langsmith), AI platforms (e.g. Databricks, mlflow) and containerization solutions (e.g. Docker) is valued. Strong software engineering fundamentals and proficiency in Python are a must. ...

looking for Proven ability to build and ship agentic or multi-agent frameworks into production. Expert Python, FastAPI, and asyncio developer. Practical experience with LangChain, Autogen, or custom orchestration layers. Startup mindset: ownership, speed, and pragmatism over perfection. Bonus points Experience working with voice or streaming systems (STT/ ...

with sensitive data. You'll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you'll do Research, prototype … MLflow for experiments, deployment, and monitoring What you'll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark/Kafka and End-to-end pipeline experience Databricks, MLflow, Docker, Kubernetes Clear communication with technical and non-technical stakeholders ...