26 to 42 of 42 LangSmith Jobs in London

also have: Extensive practical experience within AI engineering, particularly involving large language models. Strong proficiency in Python and production-level software development. Experience using LangSmith, Braintrust, Arize or similar AI observability and evaluation platforms. A strong understanding of LLM backend architecture and AI operations. Experience building data platforms and supporting ...

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 ...

open-source models — with fallback routing, token, cost, and latency managementImplement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoringEmbed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with ...

from idea to production and keeping them running.Modern GenAI tooling – You have hands-on experience with libraries and tools like Pinecone, HuggingFace, LangChain/LangSmith, or CrewAI, and you know how to pick the right tool for the job.Understanding of agentic architectures – You're comfortable designing systems involving tool ...

practical experience.Willingness to travel if needed to offshore teams (approximately 5 days per year).Preferred Skills and ExperienceISTQB/ISEB Advanced level certification.Familiarity with LangSmith, DeepEval, Ragas, Promptfoo, or similar tools.Experience with Agentic workflows, RAG applications, or AI evaluation pipelines.Cloud certification (AWS, GCP, Azure).Track record of successful automation initiatives.Understanding ...

e.g., LangGraph, Claude Agent SDK, OpenAI Agents SDK), MCP-based integrations, or multi-agent architectures.Familiarity with evaluation and observability tooling for LLM systems (e.g., LangSmith).Exposure to SAP or large-scale enterprise transformation programmes.Experience contributing to practice growth: proposals, business development, or capability building.Advocacy of AI-native engineering tools (e.g. ...

LangGraph/LangChain agent sub‐graphs and multi‐step workflows.LLM Integration: Improve prompt engineering, orchestrate multiple models, and implement tool‐calling logic.System Observability: Use LangSmith or equivalent tracing/logging to monitor agent behaviour and performance.Benchmarking & Evaluation: Contribute to LLM benchmarking across tasks and model families.API Engineering: Build and consume ...

GenAI capabilities Strong candidates might also have: Experience fine-tuning models for style or persona (e.g. chatbots with specific character voices) Exposure to LangSmith or similar observability tools for prompt/LLM testing Knowledge of voice synthesis, cloning, or emotion conditioning in audio pipelines Previous work in media, journalism, podcasting ...

selections for individual AI systems, defining memory strategies, orchestration patterns and tool integration methods. Implementing robust evaluation frameworks (using DeepEval, Arize Phoenix, Galileo, or LangSmith) to define and measure AI quality, safety and fairness before systems go live. Engineering advanced context pipelines, leveraging chunking, hybrid search, re‐ranking, knowledge graphs ...

boundaries of GenAI capabilitiesStrong Candidates Might Also HaveExperience fine-tuning models for style or persona (e.g. chatbots with specific character voices)Exposure to LangSmith or similar observability tools for prompt/LLM testingKnowledge of voice synthesis, cloning, or emotion conditioning in audio pipelinesPrevious work in media, journalism, podcasting, or content ...

Comfortable working in ambiguity and pushing the boundaries of GenAI capabilities; Nice to have: Experience fine-tuning models for style or persona, exposure to LangSmith or similar observability tools, knowledge of voice synthesis or cloning, experience in media or content production, familiarity with multimodal generation, contributions to open-source ...

makingTrack record of mentoring others and elevating team capabilitiesNice to Have:Treasury, fintech, or payments domain knowledge (cash positioning, FX, liquidity).LLM observability tools: LangSmith, Arize, Weights & Biases.AWS (S3, Glue, Redshift, Lambda); TMS/financial data providers (Bloomberg, Kyriba).Startup, founder, or cross-functional multi-product experience.Our Benefits:Paid Vacation ...

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 ...

have Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e-commerce or retail environments. Charlotte Tilbury is a fast‐paced, dynamic ...

Senior Machine Learning Engineer ££75,000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Senior Machine Learning Engineer Location: London (Hybrid) Salary: £75,000 + Bonus + Excellent Benefits Are you ...

Vacancy detailSenior Machine Learning Engineer75,000 GBPHybrid WORKINGLocation: Central London, Greater London – United Kingdom Type: PermanentSenior Machine Learning EngineerLocation: London (Hybrid)Salary: 75,000 + Bonus + Excellent BenefitsAre you passionate about applying Machine Learning ...

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 ...