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Build and ship AI-powered features like LLM agents and event intelligence for a large-scale incident management platform, working with LLMs, retrieval, and distributed systems.
The AI Engineer will develop and orchestrate GenAI models and RAG applications using Python, LangChain, Haystack, and LlamaIndex. The role involves building backend logic, integrating APIs, and automating workflows to solve business process requirements.
Senior AI Engineer building AI agent solutions for risk management and payment processing at Airwallex, using Python, ML frameworks (PyTorch/JAX), and agentic frameworks like LangChain and LlamaIndex.
Lead the architecture and development of RAG systems combining LLMs with industrial knowledge sources to build troubleshooting assistants, using Python, PyTorch, Hugging Face, LangChain, and vector databases.
Senior AI/ML Engineer designing, optimizing, and validating enterprise-grade LLM and RAG solutions in Python, leading technical audits, building evaluation frameworks, and mentoring teams.
Lead a team to design, build, and deploy AI/ML systems including LLMs, RAG, and agentic workflows, setting engineering standards and ensuring production-grade reliability and governance.
Leads a GenAI team to develop fraud detection models and AI-driven solutions, blending technical expertise in Python, LLMs, and MLOps with leadership to scale data science initiatives in fintech.
Embed with enterprise customers to prototype and deploy full-stack AI/ML solutions on Cloudera, turning complex data into actionable insights using modern AI stacks.
Data Scientist designing and implementing end-to-end generative AI and LLM solutions, working across the full software development lifecycle with NLP/CV, Python, and cloud platforms (Azure, AWS, GCP).
Role Summary As a Full Stack Engineer (Agentic AI), you will be at the forefront of building cutting-edge AI-powered applications using modern technology stacks. This position involves working with multi-agent…
Build and lead AI-powered developer tools—automated PR reviewers, code-quality gates, test generation, and codebase-aware agents—integrating them into Slack, Git, CI/CD, and IDEs using Python, Docker, Kubernetes, and LLM/agent frameworks.
KPMG is currently seeking a UI Developer (Assistant Manager) Responsibilities: Expert in building large scale secure chat-based web applications Expert is building responsive, accessible, high-performance web…
Senior AI Engineer2 Technical Skills Engineering Stack: Strong hands-on proficiency in Python and/or .NET (C#, Core) , Java , or Node.js . AI & GenAI: Practical experience with GenAI APIs (OpenAI, Azure OpenAI),…
Career Category Information Systems Job Description ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover,…
Description Digitain is seeking a highly skilled and strategic Lead AI Automation Engineer to drive the next generation of intelligent process automation across our enterprise ecosystem. In this role, you will lead the…
Forward Deployed Engineer embedding with client teams to deploy, integrate, and scale enterprise Generative AI solutions on Google Cloud Platform, working with LLMs, vector databases, RAG pipelines, and GKE infrastructure.
Senior forward-deployed engineer embedded with Carlyle's Finance and Fund Management teams, building full-stack AI/automation solutions for Global Wealth operational processes (NAV reporting, fee models) using AWS services, LLM/RAG architectures, and modern frontend/backend frameworks.
This role involves designing and developing production-grade Agentic AI systems for financial platforms at Citi. The engineer will build multi-agent architectures, optimize RAG pipelines, and integrate LLMs to automate complex financial decision-making workflows.
This role involves designing and integrating generative and agentic AI solutions into enterprise platforms using Python, RAG, and multi-agent orchestration frameworks. The developer will focus on architecting scalable AI systems, including knowledge graphs and agent harnesses, to enhance operational efficiency.
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