11 of 11 LangSmith Jobs in the UK excluding London

Docker**, **Kubernetes**, and **Docker Compose**.* **Infrastructure as Code (IaC)**: Exposure to tools like **Terraform**.* **Monitoring Tools**: Familiarity with LLM monitoring tools like **Langsmith**, **Langfuse**, or similar.* **CI/CD**: Experience with continuous integration and deployment tools such as **GitLab**, **GitHub**, or **Jenkins**.## **Database Management*** Vector Databases: Experience ...

Docker**, **Kubernetes**, and **Docker Compose**.* **Infrastructure as Code (IaC)**: Exposure to tools like **Terraform**.* **Monitoring Tools**: Familiarity with LLM monitoring tools like **Langsmith**, **Langfuse**, or similar.* **CI/CD**: Experience with continuous integration and deployment tools such as **GitLab**, **GitHub**, or **Jenkins**.## **Database Management*** Vector Databases: Experience ...

production not just proofs of concept. Cloud & MLOps fluency: AWS/GCP/Azure, containerization, serverless architectures, and MLOps/LLMOps tooling (Weights & Biases, LangSmith, MLflow). A product‐first mindset: Fluency with evaluation frameworks (Ragas, DeepEval) and a track record of managing latency, cost, and hallucination tradeoffs ...

designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication and stakeholder management skills Ability to translate complex technical concepts into business value ...

Code as an autonomous SDLC agent: sub‐agents, hooks, custom skills, agent marketplaces, context sharing across a team. LLM observability and tracing tooling (LangFuse, LangSmith, Arize, Braintrust or similar). Regulated‐environment delivery: HIPAA, GDPR, SOC 2, FCA/PRA, PII handling, data residency, guardrails and red‐teaming. Graph ...

Production Python engineering : Clean, modular, testable, maintainable code — you care about system reliability as much as model output. Evaluation & observability : Practical experience instrumenting tracing (LangSmith, Arize) and building CI/CD pipelines built specifically for LLMs. Engineering foundations : Distributed systems, scalable data pipelines (Kafka, SQL), and cloud‐native infrastructure. Cloud ...

backend layersGood-to-Have SkillsExperience designing internal developer platforms or AI enablement tooling at scaleKnowledge of prompt engineering, evaluation frameworks, and LLM observability (e.g., LangSmith)Familiarity with MLOps — model versioning, monitoring, and drift detectionBackground in platform engineering — GitOps, service mesh, infrastructure as code (Terraform/CDK)Experience with multi-cloud ...

Company DescriptionWe believe in the power of ingenuity to build a positive human future. As strategies, technologies, and innovation collide, we create opportunity from complexity. Our teams of interdisciplinary experts combine innovative thinking and breakthrough ...

production monitoring for AI‐native systems. What you’ll be doing: Design and build eval and observability pipelines using platforms such as Braintrust, LangSmith, Arize, or Weights & Biases. Curate golden datasets and design LLM‐as‐judge and human‐in‐the‐loop scoring pipelines. Build production observability for AI features: token … talk to you if you: Have strong Python skills and hands‐on AI engineering experience, particularly around evals and observability. Have used Braintrust, LangSmith, Arize, Weights & Biases, or a similar platform in production. Are comfortable designing scoring pipelines and know how to sanity‐check whether a score means anything. Have ...

production monitoring for AI‐native systems. What you’ll be doing: Design and build eval and observability pipelines using platforms such as Braintrust, LangSmith, Arize, or Weights & Biases. Curate golden datasets and design LLM‐as‐judge and human‐in‐the‐loop scoring pipelines. Build production observability for AI features: token … talk to you if you: Have strong Python skills and hands‐on AI engineering experience, particularly around evals and observability. Have used Braintrust, LangSmith, Arize, Weights & Biases, or a similar platform in production. Are comfortable designing scoring pipelines and know how to sanity‐check whether a score means anything. Have ...

production monitoring for AI‐native systems. What you’ll be doing: Design and build eval and observability pipelines using platforms such as Braintrust, LangSmith, Arize, or Weights & Biases. Curate golden datasets and design LLM‐as‐judge and human‐in‐the‐loop scoring pipelines. Build production observability for AI features: token … talk to you if you: Have strong Python skills and hands‐on AI engineering experience, particularly around evals and observability. Have used Braintrust, LangSmith, Arize, Weights & Biases, or a similar platform in production. Are comfortable designing scoring pipelines and know how to sanity‐check whether a score means anything. Have ...