8 of 8 Permanent LangSmith Jobs in the North of England

Protocol (MCP)• Evaluation engineering (golden datasets, regression gates in CI, LLM-judge calibration)• Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure ...

Docker Compose.* Infrastructure as Code: Proficiency with Terraform or equivalent.* Evaluation and Monitoring: Experience with evaluation-driven development and LLM observability tooling such as Langsmith, Langfuse, Braintrust, or similar.* CI/CD: Comfortable owning pipelines end to end (GitHub Actions, GitLab CI, Jenkins).* Database Management: Experience with vector databases ...

modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK. WHAT YOU'LL LOVE ABOUT WORKING HERE We’re a fantastic team of bright, ambitious ...

modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens.* Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK.## **WHAT YOU'LL LOVE ABOUT WORKING HERE**We’re a fantastic team of bright, ambitious ...

source models — with fallback routing, token, cost, and latency management Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities ...

source models — with fallback routing, token, cost, and latency management Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities ...

source models with fallback routing, token, cost, and latency management Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities ...

stack. You will collaborate with client engineering teams, lead technical design sessions, and create reusable patterns that scale across engagements, with exposure to LangGraph, LangSmith, and multiple LLM providers. #J-18808-Ljbffr ...