deployment of LLMs via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval Implementation of grounding, context injection, and response validation mechanisms Model Context Protocol (MCP) Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual More ❯
deployment of LLMs via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval Implementation of grounding, context injection, and response validation mechanisms Model Context Protocol (MCP) Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual More ❯
and scaling multi-agent systems or tool-augmented LLM workflows. Familiarity with secure cloud development practices and IAM role design. Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). Exposure to contact centre automation, conversational agents, or RAG pipelines. Adecco is a disability-confident employer. It is important to us that we run an inclusive and More ❯
and scaling multi-agent systems or tool-augmented LLM workflows. · Familiarity with secure cloud development practices and IAM role design. · Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). · Exposure to contact centre automation, conversational agents, or RAG pipelines. Please click here to find out more about our Key Information Documents. Please note that the documents More ❯
attention to detail, and a collaborative, growth-focused mindset. Experience working in agile, product-driven engineering teams. Preferred Qualifications: Exposure to Retrieval-Augmented Generation (RAG) pipelines, vector databases (e.g., Pinecone, Weaviate, Milvus), and knowledge bases, with familiarity in integrating them with LLMs. Experience with advanced model monitoring, observability, and governance of LLMs and generative AI systems. Experience with data engineering More ❯
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 Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS More ❯
patterns specific to RAG (Retrieval-Augmented Generation), Graph RAG, Agentic RAG, and multi-agent systems. Vector Databases & Embeddings: Expertise in working with various embedding models and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS). Advanced AI Concepts: Strong grasp of advanced techniques such as complex task decomposition for agents, reasoning engines, knowledge graphs, autonomous agent design, and evaluation methodologies for More ❯
APIs/services. Strong skills in MLOps: containerisation (Docker, Kubernetes), cloud deployment (AWS, GCP, Azure), and CI/CD pipelines. Experience with prompt engineering, LLM evaluation, and vector databases (Pinecone, Weaviate, FAISS). Excellent communication skills and cross-functional collaboration experience. Benefits: Our team at OneClickComply is central to our 100% customer satisfaction, and we offer some of the best More ❯
or Azure proficiency Containers & IaC: Docker, Kubernetes, Docker Compose, Terraform Monitoring: Langsmith, Langfuse, or similar CI/CD: GitLab, GitHub, Jenkins Databases: SQL (PostgreSQL), NoSQL (MongoDB), vector DBs (ChromaDB, Pinecone, Qdrant, etc.) Professional Skills: Experience working in agile delivery environments Excellent communication and stakeholder management Demonstrated leadership in project delivery or team management Eligible for or holding active SC (Security More ❯
LLM/agent-based prototypes (e.g., copilots, chatbots, A2A agents). Implement multi-step reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). Build UIs (Streamlit, Gradio, React) and integrate APIs and databases. Preferred More ❯
skills and ability to work in a team environment. Preferred Qualifications: Experience working with large-scale AI applications and personalization engines. Familiarity with production-scale vector databases (e.g., QDrant, Pinecone, Weaviate). Understanding of AI model interpretability and ethical AI considerations. Exposure to real-time AI applications and MLOps workflows. Why Join Us? Work alongside industry experts on cutting-edge More ❯
Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding of data paradigms for LLMs, RAG architectures, and how data pipelines support fine-tuning or pre-training. MLOps Principles More ❯
internal workflows using Azure or Vertex AI, with secure data handling. Implement ISO-aligned controls, monitor infrastructure, and respond to cloud security incidents. Work with tools like Airflow, Dataflow, Pinecone, and ElasticSearch to manage secure data flows. What You'll Need 3+ years in DevSecOps, DevOps, or Site Reliability Engineering , with a strong security background. Expertise in GitHub Actions, Terraform More ❯
largescale transformer models (BERT, GPT) and promptengineering for sentiment tasks Background building activelearning and annotation pipelines to bootstrap training data Familiarity with semantic search or vector databases (Elasticsearch, FAISS, Pinecone) for topic modeling and similarity queries Familiarity with crypto markets, order books, and risk-management frameworks Familiarity with anomalydetection methods for streaming text and timeseries data Experience developing EVM smart More ❯
DevOps tools such as GitHub Actions, Azure DevOps, or Terraform. Understanding of search technologies like Elasticsearch, Meilisearch, or Typesense. Experience working with vector search or hybrid search (e.g. pgvector, Pinecone). Knowledge of Microsoft Entra ID/Azure AD and web authentication protocols (OAuth, OpenID Connect). Experience with serverless functions, real-time systems, or edge computing. We are united More ❯
