compliance considerations in AI, especially within financial services and other regulated industries. Experience Hands-on experience with leading ML frameworks (e.g., PyTorch, TensorFlow) and LLM libraries (e.g., Hugging Face, LangChain/LangGraph, LlamaIndex). Practical experience implementing CI/CD pipelines using tools like GitHub Actions or Jenkins, and managing MLOps and LLMOps with MosiacAI, MLflow, Sagemaker or similar platforms. More ❯
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 ❯
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 ❯
on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time More ❯
etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client’s existing enterprise stack. Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph). Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS More ❯
etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client’s existing enterprise stack. Hands-on mastery of core GenAI frameworks (e.g., LangChain, LlamaIndex) and practical experience with Agentic AI frameworks and concepts (e.g., AutoGen, CrewAI, LangGraph). Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS More ❯
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 ❯
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 ❯
Edinburgh, Scotland, United Kingdom Hybrid / WFH Options
Luxoft
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 ❯
City of London, London, United Kingdom Hybrid / WFH Options
Luxoft
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 ❯
Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine-tuning, and evaluation. Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major More ❯
Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine-tuning, and evaluation. Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Oliver James
Experience in one or more business domains such as finance, housing, operations, or customer service. Preferred Extras: Degree in Computer Science, AI, Data Science, or related fields. Experience with LangChain, CrewAI, Autogen, MLOps, CI/CD, and enterprise systems like SAP, Oracle, or Salesforce. How You'll Measure Success Number of intelligent agents deployed and adopted. Significant reduction in manual More ❯
Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle More ❯
Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). Generative AI features: embeddings, RAG, AI agents. Clean, testable code with modern engineering practices. Align with enterprise architecture and governance. Collaborate with architects and stakeholders. Lifecycle More ❯
Data & AI strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. * Clean, testable code with modern engineering practices. * Align with enterprise architecture and governance. * Collaborate with architects and stakeholders. * Lifecycle More ❯
City of London, London, United Kingdom Hybrid / WFH Options
develop
prototype new techniques in AI orchestration and agentic reasoning What We’re Looking For Proven experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative More ❯
prototype new techniques in AI orchestration and agentic reasoning What We’re Looking For Proven experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative More ❯
Demonstrable experience delivering AI, LLM, or data-driven applications Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn) and/or TypeScript/JavaScript Familiarity with LLM frameworks (LangChain, LlamaIndex) and vector databases (Pinecone, Weaviate) Understanding of cloud platforms (AWS, Azure, or GCP) and modern development workflows (Git, CI/CD) Excellent problem-solving skills and a proactive, collaborative More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
Demonstrable experience delivering AI, LLM, or data-driven applications Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn) and/or TypeScript/JavaScript Familiarity with LLM frameworks (LangChain, LlamaIndex) and vector databases (Pinecone, Weaviate) Understanding of cloud platforms (AWS, Azure, or GCP) and modern development workflows (Git, CI/CD) Excellent problem-solving skills and a proactive, collaborative More ❯
identifying and mitigating security vulnerabilities during development. Experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines, working with LLM APIs (AWS Bedrock, OpenAI, Azure OpenAI), and using frameworks like LangChain or LangGraph. Strong knowledge of SDLC principles, CI/CD pipelines, and modern engineering practices. Excellent communication and collaboration skills to partner across engineering, product, and governance teams. Bachelor's More ❯
proficiency in Python for backend and AI development Experience with Go is highly desirable Hands-on experience building AI agents and integrating them into production systems Practical knowledge of LangChain, LlamaIndex, and LangGraph for LLM orchestration and data retrieval Experience with LLM fine-tuning, prompt engineering, and API integration (e.g., OpenAI, Anthropic, Gemini) Solid understanding of cloud infrastructure (AWS, GCP More ❯
proficiency in Python for backend and AI development Experience with Go is highly desirable Hands-on experience building AI agents and integrating them into production systems Practical knowledge of LangChain, LlamaIndex, and LangGraph for LLM orchestration and data retrieval Experience with LLM fine-tuning, prompt engineering, and API integration (e.g., OpenAI, Anthropic, Gemini) Solid understanding of cloud infrastructure (AWS, GCP More ❯
or product architectures Stay current with emerging AI frameworks, libraries, and model optimisation techniques What We’re Looking For Strong Python and ML ecosystem experience (PyTorch, TensorFlow, Hugging Face, LangChain, etc.) Proven delivery of AI/ML solutions in production environments Experience with cloud platforms (Azure, AWS, or GCP) and MLOps tooling (MLflow, Vertex AI, etc.) Ability to communicate clearly More ❯
