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Senior AI/ML Engineer defining architecture, standards, and governance for AI/ML platforms, agent frameworks, and MCP strategy within Network Intelligence at an ISP, primarily using Python, LLMs, and agentic orchestration technologies.
Thiết kế và xây dựng các sản phẩm/tính năng AI: trợ lý truy vấn, tổng hợp, thống kê, so sánh và phân tích dữ liệu thị trường, ngành, mã chứng khoán; xử lý và tóm tắt báo cáo, tài liệu; chatbot/trợ lý nghiệp vụ cho…
About Us 🚀 Bridgit is a leading non-bank lender transforming the way Australians access property equity. Purpose-built to make property transactions faster and easier, we pioneered the Buy Now, Sell Later solution —…
Designs and builds enterprise-scale Agentic AI platforms for autonomous AI agent development, deployment, monitoring, and governance using Azure AI, LangChain, and Python.
The Senior AI/ML Engineer will design and deploy enterprise-scale AI systems, including intelligent agents and copilots, using Python, LLMs, and RAG architectures. The role focuses on building scalable, production-grade AI services within a cloud-native environment.
Required Skills 8–11 years of software engineering experience Strong expertise in TypeScript and Node.js Strong programming experience in Python Hands-on experience with LLMs and Generative AI Experience with AI…
Design and deliver enterprise-grade generative AI solutions using Azure OpenAI, LangChain, and RAG pipelines to build AI agents and scalable AI infrastructure.
Senior Forward Deployed Software Engineer on ServiceNow's Applied AI team, building and deploying production LLM-powered applications end-to-end for strategic enterprise customers in London, spanning backend services, orchestration pipelines, and front-end integrations.
Build secure .NET applications powered by LLMs and Azure AI services, implementing RAG pipelines and cloud-native services on Microsoft Azure.
Salary: £80,000 - 100,000 per year Requirements: Strong Python development experience building production AI applications. Proven experience developing Agentic AI, LLM, and RAG solutions. Experience with frameworks…
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.
Develop and evolve scalable microservices using Java/Kotlin and Spring Boot, integrating traditional systems with Generative AI ecosystems in the financial sector.
About the Role: The team: Our Engineering team develops and maintains modern, cloud-based applications and AI-powered solutions that support global business operations. Team members collaborate across Product,…
At Signature Aviation, we are modernizing operations and customer experiences through advanced data platforms and artificial intelligence. We are seeking a Principal Engineer – AI Agentic Systems to design, architect,…
Architect and build production-grade GenAI systems including RAG pipelines, LLM integrations, and agentic applications using Python, FastAPI, vector databases, and cloud platforms (AWS/Azure) at a data analytics scale-up.
AI Engineer at Barclays building full-stack GenAI solutions (LLMs, RAG, vector stores) using Python or Java with React/Angular, delivered via cloud-native DevSecOps with Docker, Kubernetes, and CI/CD.
Lead Software Engineer building Generative AI solutions—assistants, AI-infused pipelines, and tooling—using Python/Go, deployed on AWS with GitHub Actions CI/CD, leveraging frameworks like LangChain and LangGraph at Caterpillar's Cat Digital division.
Senior Software Engineer building Generative AI solutions—assistants, processing pipelines, and tooling—using Python/Go, LangChain/LangGraph, and deploying on AWS with GitHub Actions CI/CD at Caterpillar's Cat Digital division.
Lead AI Back-End Engineer designing and scaling an LLM-powered agent platform using Python/C# APIs, Semantic Kernel, and retrieval systems like pgvector/Azure AI Search. Focuses on agent orchestration, cost/latency optimization, and mentoring engineers.
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