16 of 16 Permanent LangChain Jobs in Slough

skills in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps More ❯

are comfortable in a demo environment, writing simple scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience More ❯

Augmented Generation (RAG), and graph databases Familiarity with multi-agent LLM systems and agentic platforms (e.g., AutoGen, CrewAI), and experience deploying LLM-based applications Experience with tools such as LangChain, LangSmith, or Chainlit Exposure to event-driven architectures, asynchronous processing, and tools like Celery or Kafka Familiarity with CI/CD pipelines, Docker, and DevOps workflows Experience designing or integrating More ❯

and scaling ML systems in production environments. · Experience training or applying machine learning models (LLMs or predictive models), with a strong grounding in scientific and statistical methodology. · Familiarity with LangChain, PydanticAI, AutoGen, or similar frameworks for building LLM agents and pipelines. · Software engineering experience, including collaborative development (Git/GitHub), deployment tooling (e.g., Docker, Kubernetes, CI/CD), and good More ❯

ML, data engineering, or automation use cases Experience working with or building applications around large language models (open-source or commercial) Familiarity with LLM agents, orchestration frameworks (e.g. LangGraph, LangChain), and context management Experience with cloud platforms (AWS preferred) and associated services for AI workloads A background in software engineering or data science, ideally in a research-driven or exploratory More ❯

in AI, natural language processing, or data visualisation. Adaptability and willingness to learn in a fast-paced startup environment. Nice to have: Familiarity with workflow automation tools (e.g. n8n, LangChain) or BI platforms (QuickSight*, Tableau, Power BI). Exposure to cloud platforms (AWS, Docker) or CI/CD principles. Previous projects involving NLP, machine learning, automation, or dashboard design. Why More ❯

media agency, consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt More ❯

and solution architecture principles. Experience translating business needs into technical designs and delivering in agile environments. Excellent communication and stakeholder engagement skills. Desirable Experience with Generative AI (LLMs, RAG, LangChain, Semantic Kernel). Microsoft Power Platform exposure. Front-end experience (React, Angular, or Vue.js). Familiarity with edge computing or VR/AR technologies. What You’ll Bring Curiosity and More ❯

quickly Advising on best practices for responsible AI adoption Candidate Profile Strong experience with LLMs (e.g. GPT, Claude, LLaMA) and prompt engineering Hands-on integration with tools such as LangChain, LlamaIndex, or similar Proficiency in Python or JavaScript for building prototypes and integrations Familiarity with automation platforms (UiPath, Power Automate, Zapier, n8n) Knowledge of vector databases and embeddings for RAG More ❯

quickly Advising on best practices for responsible AI adoption Candidate Profile Strong experience with LLMs (e.g. GPT, Claude, LLaMA) and prompt engineering Hands-on integration with tools such as LangChain, LlamaIndex, or similar Proficiency in Python or JavaScript for building prototypes and integrations Familiarity with automation platforms (UiPath, Power Automate, Zapier, n8n) Knowledge of vector databases and embeddings for RAG More ❯

that’s pushing boundaries in autonomous AI What You’ll Need: A strong foundation in data science and machine learning Hands-on use of modern AI tools (LLMs, RAG, LangChain, co-pilots, agentic workflows) Curiosity and eagerness to learn in a fast-moving AI landscape Experience collaborating with stakeholders and translating business problems into technical solutions What You’ll Get More ❯

understanding of AI/ML techniques including reinforcement learning, LLM agents, and simulations Proficient in Python and Infrastructure as Code for cloud environments Familiarity with AI orchestration platforms like LangChain and LangGraph, AutoGen, CrewAI, or similar Experience supporting pre-sales in consultancy or product environments Systems thinker able to architect complex AI-integrated enterprise solutions Bonus: Experience with Microsoft Copilot More ❯

pipelines What We’re Looking For Relentless drive: You execute fast, adapt faster Startup scar tissue : You’ve shipped product with no safety net Fluency with AI/LLMs : LangChain, vector stores, prompt engineering Full-stack firepower : Frontend, backend, infra, no silos Product obsession : You care more about outcomes than outputs Experimental instinct: You build → test → learn → repeat Ideal Background More ❯

of experience in technical pre-sales, solutions consulting, or AI implementation roles. Proven hands-on experience with Generative AI, LLMs (e.g., GPT, Claude, PaLM, LLaMA), and related tools (e.g., LangChain, vector databases). Strong understanding of raw data, data structures, NLP/NLU/NLG, ML pipelines, and prompt engineering. Experience with enterprise-grade AI deployments, including model evaluation, customization More ❯

system. Expert in MCP and RAG patterns Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow) Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS) Strong background in deploying models via APIs, containers, or cloud-native services … and work across team. Minimum 5 years’ professional experience in AI, ML, or applied machine learning engineering roles. Required Skills Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow) Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS) Strong background in deploying models via APIs, containers, or cloud-native services More ❯

improve LLM-powered agents Analyze results and report findings for model improvement initiatives You bring: Strong Python skills (can read/write multi-file codebases) Working with LLM frameworks (LangChain, MCP) Experienced with Leetcode Experience with AI/ML, NLP, or generative AI research Curiosity, problem-solving mindset, and attention to detail Tech Stack needed - Languages: Python (Advanced, LeetCode-level … PHP (basic familiarity) Databases: SQL (basic–intermediate querying & analysis) AI/LLM Frameworks: LangChain, Model Context Protocol (MCP) Tools: Git/source control Concepts: Large Language Models (LLMs), prompt engineering, AI agent development 💡 This is your chance to work on AI that’s shaping the future — at a scale few companies in the world can match. More ❯