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The AI Engineer will design and operate a global AI platform, managing runtime services, RAG components, and AI governance for Allianz Technology. The role focuses on building scalable, secure, and cost-efficient infrastructure using Kubernetes, MLOps tools, and cloud-native technologies.
Привет! Это команда Возвраты ML. Мы ищем талантливого Data Scientist/ML Engineer в новую ML-команду отдела «Возвраты маркетплейса». Отдел занимается обработкой и модерацией возвратов покупателя и продавца, аннуляциями,…
Senior AI Engineer/Architect building and optimizing an AI platform by integrating LLMs (Claude, LiteLLM) into production web applications using Python, Django, JavaScript, and CI/CD pipelines.
The Lead Software Engineer will provide hands-on technical leadership to a cross-functional squad, overseeing full-stack development, architecture, and the integration of AI-powered features. The role focuses on maintaining high engineering standards, mentoring developers, and ensuring secure, scalable software delivery in a regulated environment.
Build next-gen AI models for retail using transformers and deep learning, turning research into production-ready solutions that power personalisation and forecasting.
Build and scale dunnhumby’s Enterprise AI Platform, designing production-grade AI systems including RAG, agentic workflows, and LLM-powered services using Python, LangChain, and cloud-native tools.
Build and maintain Nexxen’s internal AI platform, designing reusable AI capabilities, multi-agent systems, and production-grade AI services using Python, Kubernetes, and modern cloud-native tools.
The Principal Product Architect will serve as the technical product owner for Cyble Vision, driving the end-to-end architecture and roadmap for an AI-native threat intelligence platform. This senior individual contributor role involves collaborating across engineering, data, and AI teams to integrate LLMs, knowledge graphs, and large-scale data pipelines into customer-facing security workflows.
Senior Cloud Engineer builds and operates a Kubernetes-based AI platform, implementing SRE practices, CI/CD for AI workloads, and observability for model serving and agent systems.
Hands-on technical leadership role designing and delivering production-grade Generative AI and Agentic AI solutions, including LLM-powered applications, RAG pipelines, multi-agent architectures, and LLMOps using Python, agent frameworks, and cloud platforms.
Architect and build an enterprise-grade Agentic AI orchestration platform using Claude APIs, LangGraph, LangChain, RAG, vector databases, MCP, Python, and FastAPI in a senior technical leadership role.
Staff Data Engineer building an end-to-end data platform from scratch, designing near real-time streaming pipelines, vector database infrastructure, and AI-ready data systems using Kafka, dbt, cloud warehouses, and Python.
Full-stack AI Engineer builds and maintains the backend, AI pipelines, and frontend for Typewiser, a document intelligence platform using NLP and LLMs to improve clarity and trust in high-stakes documents.
Leads AI-driven development of insurance products by designing agentic AI systems, optimizing LLM inference, and delivering full-stack features.
Full Stack Developer building and deploying Generative AI cloud applications on Microsoft Azure, primarily using Python or .NET for backend and React/Next.js for frontend, owning the full service lifecycle.
Build and deploy cloud-based Generative AI applications using Python/.NET on Azure, with React/Next.js for frontend features, focusing on LLMs, RAG, and agent architectures.
Design and deploy AI/ML solutions—including GenAI, RAG architectures, and agentic AI—for a European financial group, using Python, LLMs, vector databases, and cloud platforms.
Intern builds and tests AI components for healthcare informatics, using LLM APIs, orchestration frameworks, and data pipelines to improve treatment, payment, and operations.
Designs and optimizes AI agentic systems (e.g., LangGraph, AWS Bedrock) for government clients, integrating LLMs with enterprise tools for workflow automation, testing, and debugging.
Designs and optimizes AI agent systems using foundation models (e.g., Claude Sonnet) to build intelligent workflows for government clients, integrating with enterprise tools and tuning agent behavior for real-world outcomes.
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