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Build and integrate AI-powered compliance and risk solutions, including LLMs, search, and workflow automation, to transform regulatory and standards data into customer value.
Build and scale a high-performance search platform using OpenSearch, Python/FastAPI, and vector search (embeddings, ANN/HNSW) to power GigaChat and LLM queries with low-latency, relevance tuning, and hybrid search.
Own the AI-powered natural-language layer for a SaaS platform: define the product strategy, architecture, and evaluation systems that let users ask questions, retrieve knowledge, and safely execute actions across CRM, automation, and workflows.
Data Scientist – Snowflake + Agentic AI / Cortex AI Primary Skills We are looking for an experienced Data Scientist with strong expertise in Snowflake and hands-on exposure to Agentic AI / Snowflake Cortex AI to join…
Build and deploy NLP pipelines using LLMs for contact-center insights, including text classification, summarization, and agentic applications in a fast-moving AI startup.
Build and deploy LLM-powered AI solutions, including RAG pipelines and NLP applications, using Python, LangChain, and cloud platforms like Azure/AWS/GCP.
Build cloud-native search and LLM-powered workflows using React, Node.js, and Elasticsearch; integrate RAG and semantic search in a secure, mission-driven environment.
Build and ship an AI-powered food agent that plans meals, sets nutrition goals, and places orders using LLMs, retrieval, and agentic workflows in production.
Build and maintain AI-powered search infrastructure for a learning platform, designing Elasticsearch pipelines, hybrid retrieval systems, and backend services to deliver low-latency, high-relevance results at scale.
Builds and maintains Databricks Lakehouse data pipelines and AI foundations for clients, designing medallion architectures, Delta Lake tables, and Unity Catalog governance to power analytics and AI-enabled products.
Define and govern enterprise AI architecture for a large U.S. utility, translating business needs into secure, scalable AI systems across grid operations and corporate functions.
Lead the design and development of enterprise AI solutions using Python, RAG, Agentic AI, and LLMs, while engineering enterprise data pipelines and integrating AI into production.
Owns the product strategy and roadmap for DDN’s AI Data Platform, aligning storage solutions with NVIDIA’s AI infrastructure stack to enable enterprise generative AI at scale.
Support and architect AI platforms for DDN’s Hyperpod, diagnosing issues across NVIDIA AI Enterprise, vector databases, GPUs, Kubernetes, and high-performance storage/networking.
Lead the design and delivery of production-grade GenAI/LLM applications for financial products, setting MLOps and responsible-AI standards while guiding engineering teams from prototyping to deployment.
Senior AI consultant designs and iterates LLM prompts, prototypes AI copilots, and builds RAG-based solutions using Python, LangChain, and vector databases for enterprise use cases.
Leads AI initiatives, designs and iterates prompts for enterprise copilots and low-code tools, and prototypes generative AI solutions using Python, LangChain, and vector databases.
Build and run the AI platform powering a conversational assistant, focusing on RAG pipelines, LLM orchestration, and vector search on Microsoft Azure and Foundry.
Build and deploy enterprise AI solutions—LLMs, RAG, and agentic systems—using Python and Azure to improve customer outcomes and operational efficiency in a regulated financial services environment.
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