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Build and own scalable backend services in Node.js/TypeScript that integrate AI models and data pipelines for banking clients, deploying on Azure/AWS.
The Lead Data Scientist will oversee the enterprise AI strategy, managing teams focused on Generative AI, MLOps, and machine learning applications for HVAC and data center operations. This role involves leading the end-to-end AI lifecycle, from experimentation to production, while aligning technical initiatives with business goals.
The Lead AI Engineer will architect and build autonomous, production-grade agentic systems using Python, LangGraph, and various LLM orchestration frameworks. This role involves designing multi-agent workflows, managing state for long-running tasks, and integrating real-time data pipelines to enable intelligent, self-healing decision-making systems.
The Generative AI Engineer will design, develop, and deploy scalable AI solutions using LLMs and transformer architectures. The role involves orchestrating model workflows, integrating GenAI into enterprise systems, and collaborating with MLOps teams on cloud platforms.
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.
The Lead AI Engineer will architect and build production-grade autonomous agentic systems using Python, LangGraph, and various LLM orchestration frameworks. This role involves designing multi-agent workflows, managing state for long-running tasks, and integrating real-time data pipelines to support intelligent, self-healing applications.
Summer internship at Cisco Bangalore for 2028 batch Master's students, working on networking protocols, embedded systems, or cloud application development using C/C++, Python, Java/Go/React, with a strong emphasis on AI-assisted development workflows.
The Senior Data Science Engineer will develop and implement Agentic AI solutions and mathematical models to optimize supply chain and business operations. The role involves building autonomous systems using frameworks like LangGraph and integrating LLM APIs to deliver actionable insights and data-driven products.
The Senior AI Machine Learning Engineer will design and deploy production-grade generative AI applications and autonomous agents to automate financial workflows. The role focuses on leveraging foundation models, RAG, and fine-tuning to enhance BlackLine's financial close and invoice-to-cash platforms.
Design and build agentic AI solutions—LLM-powered agents, RAG pipelines, and workflow automation—integrated with CRM/PMS systems for a property portfolio platform, using Python/C#/TypeScript, vector databases, and frameworks like LangChain or Semantic Kernel.
Develop and evolve generative AI solutions, intelligent agents, and RAG architectures at Senior Sistemas' AI Core, using Python, LLMs, vector databases, and cloud platforms in a hybrid role based in Blumenau/SC.
Lead the design and implementation of enterprise-grade Generative AI and Agentic AI solutions—spanning RAG, LLMs, and AI agents—using frameworks like LangChain, LangGraph, vector databases, and cloud-native infrastructure on a 12-month contract.
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.
Hands-on AI Engineer designing, building, and deploying LLM/GenAI solutions covering the full AI lifecycle including RAG pipelines, agentic AI, model training/fine-tuning, and production deployment using Python.
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.
The Lead Data Scientist will architect and develop autonomous AI agents capable of goal setting and decomposition for healthcare applications. The role involves designing planning systems, implementing evaluation frameworks, and ensuring agent reliability using technologies like Python, PyTorch, LangChain, and large-scale ML pipelines.
Design and deploy production-ready generative AI solutions and autonomous agents using Python, LLMs, and frameworks like LangChain, while partnering with MLOps and business stakeholders at a healthcare company.
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.
Design and deploy production-grade agentic AI solutions using Python, LLMs, and agent frameworks like LangChain/LangGraph, collaborating directly with client engineering and product teams in a client-facing delivery role.
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