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Senior AI engineer embeds and deploys enterprise-grade AI systems for clients, building LLM/RAG pipelines, agents, and ML models while navigating compliance and legacy systems.
Build and maintain the FinFAST platform’s full-stack features, integrating LLM APIs for an AI research assistant and creating interactive dashboards to visualize economic data.
Build and deploy AI agents that solve real workflow problems for energy traders, bridging commercial needs with engineering and shaping Vitol’s GenAI platform.
Build and deploy NLP models (Transformers, LLMs) for text analysis, RAG, and multi-agent systems on a cloud-native data-processing platform handling 10M events and 10TB daily.
Job Description Education and Work Experience Requirements: · 5 to 8 years of experience as Data Scientist or GenAI specialist· 2 to 3 years of experience in Generative AI solution development· Proven track record and…
Education and Work Experience Requirements: · 5 to 8 years of experience as Data Scientist· 2 to 3 years of experience in Generative AI solution development· Strong understanding of AI agent collaboration, negotiation,…
Design and lead enterprise-scale AI and data architectures, integrating LLMs, RAG, and agentic systems with cloud platforms like AWS, Azure, and Google Cloud.
Build and deploy AI-powered healthcare solutions using LLMs, RAG, and Azure services to automate document processing and enhance clinical insights for payors and providers.
Build production-grade AI architecture blueprints and open-source Quickstarts with Python, PyTorch, and Kubernetes, focusing on enterprise deployment, security, and regulated environments.
Build AI-powered multi-agent systems and full-stack applications using Node.js, React, and TypeScript, integrating LLMs, vector databases, and observability tools like Langfuse for agentic workflows and dashboards.
Lead a team to design, build, and deploy AI/ML models (computer vision, GenAI, NLP) using TensorFlow/PyTorch and MLOps practices, while mentoring engineers and owning full model lifecycles.
Build and deploy AI/ML models (LLMs, NLP, vision, recommender systems) as scalable microservices, working with cloud partners and business teams to drive data-driven decisions.
Build and deploy GenAI and agentic AI systems for pharma clients using Microsoft Copilot Studio, ChatGPT Enterprise, and AWS Bedrock, integrating structured and unstructured data pipelines.
Build and deploy production-ready AI and multi-agent systems for healthcare, focusing on secure, compliant generative AI workflows using LLMs, RAG pipelines, and cloud platforms.
Lead a team building enterprise-grade AI/ML solutions for financial data operations, including LLMs, RAG, and multimodal models, while driving MLOps/LLMOps and cloud deployments.
Lead enterprise GenAI strategy, architect scalable AI systems, and advise C-suite on tech stacks, trade-offs, and ROI for large client engagements.
Lead a team building AI-powered cloud systems at JPMorganChase, integrating LLMs, RAG pipelines, and agentic workflows while leveraging AI coding assistants daily.
Lead a team of NLP engineers to build LLM assistants, intelligent search, and document processing for a top-5 Russian bank using fine-tuning, RAG, and vector databases.
Build and deploy LLM-powered applications for federal clients, implementing RAG pipelines, prompt engineering, and production AI infrastructure using Python, FastAPI, and cloud services.
Build and optimize production-grade AI systems using RAG pipelines, vector stores, and cloud-native tools to deliver secure, scalable solutions for federal environments.
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