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The AI Application Engineer builds production-ready, user-facing AI applications and copilots for enterprise clients using Python, LLMs, RAG, and cloud infrastructure. The role involves bridging the gap between AI model development and scalable backend deployment to solve real-world business challenges.
Designs and deploys scalable AI/ML systems, including GenAI and computer vision, while leading reusable frameworks and mentoring teams to raise technical standards across projects.
Чем предстоит заниматься: Разработка и оптимизация RAG-систем на базе LLM (LLaMA, GPT-подобные модели) для обработки внутренних документов, отчётов и регламентов ключевых заказчиков; Реализация и тонкая настройка…
Ключевые задачи: Разработка AI‑агентов и ассистентов (чат‑боты, автоматизация процессов, аналитика) Декомпозиция бизнес‑требований в сценарии работы агентов (use cases, user flows) Проектирование логики агентов (tool…
Roles & Responsibilities Overview We are looking for a fresh graduate (degree or diploma) Data & AI Engineer to join our growing team. This is a hybrid role: about half your time will go into designing,…
AI Architect serving as enterprise design authority for AI architecture at a real estate firm, defining reference architectures, platform standards, and roadmaps focused on GenAI, LLMs, RAG, AI agents, and MLOps/LLMOps across cloud and on-prem environments.
Build and deploy ML/LLM solutions end-to-end for diverse clients, from data prep to production APIs, while collaborating in a team of ML engineers.
Build AI Agent application modules (chat UI, knowledge bases, workflow engines) integrating LLM capabilities like RAG and tool calling, using Python/TypeScript, React/Vue, and FastAPI on a full-stack team at Surbana Jurong in Shanghai.
The Senior AI Application Developer will design, build, and deploy production-grade AI applications, including agentic systems and RAG pipelines, to support manufacturing operations. The role involves full-stack development using Python, C#/.NET, and TypeScript while implementing LLMOps practices and enterprise-grade AI governance.
Line of Service Advisory Industry/Sector Not Applicable Specialism Deals Management Level Manager Job Description & Summary At PwC, our people in deals focus on providing strategic advice and support to clients in…
Build and maintain open-source AI/ML platforms at Databricks to enable users to train, deploy, and monitor models and GenAI agents at scale, primarily using Python, with collaboration across the AI/ML community.
Build and maintain Python-based backend services and AI-powered chatbots, integrating LLMs and RAG workflows to deliver scalable, production-grade applications.
AI Engineer in EY's consulting practice in Singapore, building and deploying GenAI/LLM-powered multi-agentic applications, NLP models, and end-to-end AI workflows using Python, cloud platforms (Azure, AWS), and frameworks like LangChain and LlamaIndex.
Role Mission Own the translation of business problems into production-ready LLM applications. This role designs the application logic around the model: prompt architecture, context management, tool calling, RAG…
Build and deploy agentic AI/ML applications on AWS for national security missions, using Python, large language models, RAG architectures, and agent orchestration patterns to automate workflows and support decision-making.
Develops and deploys AI-powered legal tools by designing experiments, evaluating LLM/ML models, and prototyping agentic systems for legal research, drafting, and decision-making.
Designs, builds, and evaluates AI agents and LLM-powered systems (RAG pipelines, tool-use workflows) using Python to automate multi-step research and clinical-support tasks at a medical center.
About this role: Wells Fargo is seeking a Quantitative Analytics Manager. Wells Fargo is seeking a hands-on Manager for oversight of development of Foundation models as well as Gen AI and Agentic applications…
Design, build, and operationalize LLM-powered applications, RAG systems, and intelligent agents for automotive industry use cases, spanning full-stack development from prototype to production using Python, React, cloud AI platforms, and vector databases.
The Principal AI Software Engineer will architect enterprise-grade AI solutions, integrating LLMs, RAG, and agent workflows into high-availability systems. The role involves leading cross-functional teams, setting technical standards for AI development, and optimizing performance and costs across cloud-based infrastructure.
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