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Senior AI Engineer builds and deploys LLM-based agents and RAG services to automate workflows and improve decision-making, owning the full GenAI product lifecycle from prototyping to production monitoring.
Lead architecture for AI-powered backend systems and public cloud platforms at Salesforce, designing resilient distributed systems and REST APIs for millions of users.
Embed with customer AI teams to design, prototype, and deploy AI agents using W&B Weave, acting as a hands-on technical advisor and troubleshooting production issues.
Build, deploy and operate AI and Generative AI solutions (agents, RAG systems, predictive models) end-to-end, including data pipelines and integrations, using Python, Azure AI, Databricks and related tools.
Builds and maintains AI-driven data pipelines and infrastructure to process, transform, and store data for LLM applications, RAG systems, and agentic AI workflows using Python, vector databases, and cloud platforms like AWS/Azure.
Обязанности: Сформировать дорожную карту ML‑инициатив для трейдинга и смежных функций (ценообразование, прогнозы спроса/предложения, оптимизация логистики, риск‑метрики); Разрабатывать end-to-end LLM-приложения : от…
Build production-grade AI systems for investment analysis and procurement using LLM, multi-agent architectures, and RAG pipelines in Python.
Senior role designing and deploying AI solutions using graph data and GraphRAG for enterprise customers, from discovery to production.
Senior AI Engineer builds and integrates LLM-powered chatbots and NLP tools to deliver data-driven insights for automotive dealerships, using Python, TensorFlow/PyTorch, and cloud platforms.
Design autonomous network solutions for telecoms using AI frameworks (Vertex AI, LangGraph), APIs, and vector databases to optimize agentic systems and reduce inference costs.
Build and deploy ML models and LLM-powered tools to improve healthcare solutions using Python, TensorFlow/PyTorch, and LangChain.
Build and deploy cutting-edge forecasting models and LLM agents for scenario planning in banking, using PyTorch, LangChain, and production-grade MLOps tooling.
Build and maintain a universal data platform that integrates enterprise data sources into automated pipelines, ensuring high-quality data for AI agents, LLMs, and RAG workflows using Python, SQL, and vector databases.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, vector/graph databases, and Kubernetes.
Build and deploy AI-powered chatbots and automation workflows using LLMs, vector databases, and no-code tools; assist in RAG systems and prompt engineering.
Build and optimize LLM-powered AI assistants for a bank’s internal support systems using Python, RAG, and vector databases.
Build and scale AI platform services like LLM gateways, MCP servers, and agent orchestration frameworks for Tekion’s cloud-native automotive platform.
Build AI agents and tools using LLMs, prompt engineering, and RAG to create applications that enhance critical thinking and societal impact.
Build and optimize LLM-powered AI assistants for a bank’s customer service channels, integrating models like GPT and Llama with internal APIs and RAG architectures.
Build and deploy AI-powered applications for U.S. government clients, integrating LLMs, vector stores, and microservices across the full stack.
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