1 to 25 of 88 Remote LangChain Jobs

and evaluation of domain-specific LLMs , applying retrieval-augmented generation (RAG) and prompt engineering techniques. Contribute to the development of multi-agent systems using frameworks such as AutoGen , LangGraph , LangChain , or CrewAI . Support the integration of AI safety techniques into system design and deployment. Help implement real-time and batch inference pipelines with secure APIs (REST/gRPC, event More ❯

platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale More ❯

platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale More ❯

Statistical testing experience Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science and generative AI methods. Exposure to generative AI application frameworks like LangChain, LlamaIndex, SmolAgents and griptape. What's in it for you? Join an ever-growing, market disrupting, global company where the teams - comprised of the best of the best - work in More ❯

in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases Strong More ❯

services or insurance sectors advantageous. Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous. Advanced proficiency in Python, and familiarity with AI frameworks such as LangChain Skilled in designing and operationalising AI Ops frameworks within cloud-based production environments. Exceptional communication skills, clearly articulating technical concepts to diverse stakeholders. Excellent organisational, time management, and prioritisation skills. More ❯

services or insurance sectors advantageous. Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous. Advanced proficiency in Python, and familiarity with AI frameworks such as LangChain Skilled in designing and operationalising AI Ops frameworks within cloud-based production environments. Exceptional communication skills, clearly articulating technical concepts to diverse stakeholders. Excellent organisational, time management, and prioritisation skills. More ❯

control (Git) Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What More ❯

SQL The ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI Skills in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI-native developer tools like Cursor, to bring ideas to More ❯

of Docker , CI/CD workflows, and automation pipelines Familiarity with MLOps tooling such as MLFlow, Git version control, and environment management Desirable Skills & Interests: Experience with frameworks like LangChain , Langflow , or similar tools for building AI agents Understanding of Large Language Models (LLMs) and intelligent automation workflows Experience building high-availability, scalable systems using microservices or event-driven architecture More ❯

governance. AI Infrastructure & MLOps: Experience with cloud AI services, model deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt More ❯

Docker, Kubernetes, NVIDIA Triton), and backend development (REST API, OpenAPI, Swagger) • Language: Fluent in written and spoken English • Nice-to-have: Experience in LLM frameworks such as Haystack/LangChain, PyTorch, and proficiency in written and spoken German Responsibilities: • Design and implement software solutions in Python and C# in the field of artificial intelligence and machine learning • Conceptualize and test More ❯

pre-trained open source models Strong understanding of machine learning workflows, including model evaluations and LLM fine-tuning Familiarity with AI orchestration and agent-based systems and best practices (LangChain, AutoGen, n8n) Excellent problem-solving skills and the ability to work independently and collaboratively. Strong communication skills and the ability to translate technical concepts to non-technical stakeholders The person More ❯

modular, distributed, and asynchronous systems Solid experience leading full-stack application development teams Expert-level proficiency in Python and hands-on experience with at least one LLM based framework (LangChain, LangGraph, LangSmith, LlamaIndex, Qdrant, etc ) Strong experience with asynchronous queues (e.g., Kafka, RabbitMQ) and asynchronous APIs Deep understanding of cloud infrastructure (AWS, GCP) and experience deploying and managing applications at More ❯

community. Engineering Design, develop, and optimize AI/ML features in Qdrant's core engine and SDKs. Prototype and implement integrations with popular ML frameworks (e.g., Hugging Face, OpenAI, LangChain). Analyze performance, identify bottlenecks, and implement scalable solutions in real-world AI pipelines. Collaborate with product and engineering teams to define and deliver impactful features. Community & Customer Engagement Support More ❯

Python and common ML/AI libraries; comfortable with full-stack system design from prototyping to production deployment. Familiarity with one or more LLM stacks (OpenAI, Hugging Face Transformers, LangChain etc) Experience with model serving frameworks and scalable deployment strategies Experience with containerisation and orchestration "Nice To Have" Skills and Experience : Exposure to hardware design or verification processes (e.g., RTL More ❯

engaging character 🎯 What We're Looking For - Essential Reqs: • PhD in Science, Machine Learning, Artificial Intelligence, Engineering, or a related field is an essential requirement • Deep knowledge of both LangChain and LangGraph • Proven experience in AI, machine learning, or data science • Strong background in designing and deploying AI solutions into production • Ability to engage with clients and shape strategic AI More ❯

GCP, Azure) Experience developing AI-driven tools. Familiarity with integrating or building chat and search interfaces, using LLMs for orchestration, vector databases, embedding models, or retrieval-augmented generation (e.g., LangChain, LlamaIndex) Strong product and communication skills. Ability to think strategically beyond tickets, clearly communicate decisions in pull requests, and discuss technical trade-offs effectively with colleagues and partners EU/ More ❯

partners to match value proposition to business needs. Thrived as a another fast-paced SaaS startup or scale-up during a high-growth phase. Preferred to have: expertise with langchain and similar tools for multimodal AI projects. What's in it for you: £80-100k base salary with £25k additional commission Top 15% quartile equity options plan through an More ❯

you to have: Experience in AI/ML engineering or applied machine learning. Proven experience delivering production-grade AI solutions. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data engineering, including feature engineering and More ❯

across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data engineering, including feature engineering and More ❯

technical requirements and solution architecture for complex AI systems. Strong experience building and consuming API services in Python, using FastAPI or similar. Strong experience with LLM frameworks such as langchain, Pydantic-AI, Google ADK, OpenAI's Assistants, litellm, etc (it's not required to know them all), and an understanding of how they facilitate agentic AI development. Strong practical knowledge More ❯

Microsoft Fabric Cloud, preferably Azure (Data Lake, Functions, App Services) Containerisation with Docker and CI/CD pipelines MLOps tooling (MLFlow, Git-based versioning, environment tracking) Desirable Skills & Interests LangChain, Langflow, or similar frameworks for building AI agents LLMs or intelligent automation workflows High-availability, scalable systems (microservices, event- based architectures) Orchestration tools like Airflow, container orchestration (Kubernetes), or serverless More ❯

Microsoft Fabric * Cloud, preferably Azure (Data Lake, Functions, App Services) * Containerisation with Docker and CI/CD pipelines * MLOps tooling (MLFlow, Git-based versioning, environment tracking) Desirable Skills & Interests * LangChain, Langflow, or similar frameworks for building AI agents * LLMs or intelligent automation workflows * High-availability, scalable systems (microservices, event- based architectures) * Orchestration tools like Airflow, container orchestration (Kubernetes), or serverless More ❯

Microsoft Fabric* Cloud, preferably Azure (Data Lake, Functions, App Services)* Containerisation with Docker and CI/CD pipelines* MLOps tooling (MLFlow, Git-based versioning, environment tracking)Desirable Skills & Interests* LangChain, Langflow, or similar frameworks for building AI agents* LLMs or intelligent automation workflows* High-availability, scalable systems (microservices, event-based architectures)* Orchestration tools like Airflow, container orchestration (Kubernetes), or serverless More ❯