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Build and deploy enterprise-grade AI applications using LLMs, RAG, and intelligent agents with full-stack development in React, Python, and FastAPI.
Builds and deploys AI agents and workflows that automate enterprise tasks across Slack, Teams, and standalone apps using Python, TypeScript, React, and integrations.
Enterprise Account Executive — Maven AGI Company Overview Maven AGI sits at the center of the hottest intersection in tech right now: AI and customer experience. While most "AI support" tools still focus on…
Designs and implements large-scale generative AI and agentic systems for enterprise clients, focusing on multi-agent architectures, RAG, and cloud integration across AWS/Azure/GCP.
Design and build a cloud-native, AI-powered self-service platform for media/advertising, integrating .NET Core APIs, React UI, and a Vertex AI agent on GCP.
Design and deploy secure, scalable AI solutions for a federal government agency using Azure AI services, agentic frameworks, and RAG to improve service delivery and align with governance requirements.
Build and deploy enterprise-grade AI/LLM solutions using Snowflake, dbt Cloud, and Python, focusing on RAG, conversational AI, and MLOps pipelines for a large pharmacy retailer.
Lead AI-powered features like chatbots and smart trading assistants for a crypto-fintech company, collaborating with ML engineers and data scientists to ship products end-to-end.
Builds and deploys production AI systems like voice hardware, conversational agents, and RAG pipelines using Python, FastAPI, and ML frameworks.
Build and test AI-powered airline tools using Python, LLMs, and agentic workflows; validate accuracy, safety, and performance of generative AI systems for aviation operations.
Build and deploy AI systems using semantic search, RAG, and multi-agent workflows with LLMs and NLP/NLU techniques in Python and cloud platforms.
Build and deploy AI systems including LLMs, computer vision, and autonomous agents using Python, PyTorch, and LangChain, then productionize them with MLOps on cloud platforms.
Designs and executes tests for an AI conversational agent, automating checks with C#/Selenium/Playwright and validating AI responses in Sierra.
Build and deploy AI-powered applications using LLMs, RAG pipelines, and vector search. Integrate LLM APIs into production systems with Python and cloud tools.
Build backend services for AI-driven banking chatbots that integrate with core systems and handle millions of secure, explainable customer interactions daily.
Build and scale an AI-driven conversational platform used by global brands, using Node.js, TypeScript, Vue.js, PostgreSQL, and Snowflake while integrating LLMs into production workflows.
Build and scale the backend platform powering real-time conversational AI for consumer apps, focusing on graph-based AI computations, multimodal services (TTS, LLM, STT), and telemetry-driven personalization.
Build and scale backend services for AI-powered voice assistants and call-center platforms using Python, LLMs, STT/TTS, and real-time voice pipelines.
Design and build enterprise-grade conversational AI systems using LLMs, RAG, and prompt engineering, ensuring security and compliance.
Designs natural, user-friendly conversational flows and AI chatbot content to improve interactions with AI-powered services.
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