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Build and deploy generative AI chatbots, predictive models, and analytics dashboards using Python, LLMs, and tools like Streamlit and Power BI.
Build and ship LLM-powered features for enterprise clients, including RAG systems, AI agents, and vector-based retrieval pipelines using Python, LangChain, and cloud tools.
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.
Build and optimize GenAI systems using LLMs, prompt engineering, RAG, and agent workflows with frameworks like LangChain. Integrate APIs, vector databases, and external tools for scalable AI solutions.
Designs the architecture for self-learning AI agents and GenAI systems, focusing on orchestration, reasoning layers, and scalable agentic workflows.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build AI-powered apps using Anthropic’s Claude API, integrating LLM workflows, prompt design, and tool use into scalable full-stack systems with React, Next.js, Node.js/Python, and vector databases.
Build full-stack web apps with React/Next.js and Node.js/PHP, integrating Anthropic’s Claude API to create AI-powered features like agents, RAG, and streaming responses.
Build and deploy AI-powered insurance workflows using LLMs and agent-based automation to process submissions, policies, and client communications.
Build and deploy multi-agent AI systems using LLM APIs (Bedrock, OpenAI, Mistral), LangGraph/LangChain, and AWS serverless tools; focus on execution, not design.
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Design and deploy AI/ML models, including LLMs and GenAI, to solve healthcare data challenges using Python, cloud platforms, and MLOps.
Build and deploy multi-agent AI systems using LLM APIs, agent frameworks, and AWS services, focusing on execution and integration rather than design.
Job Summary We are seeking an experienced AI Automation Engineering Manager to lead our AI and automation initiatives across the organization. This role is responsible for managing a team of AI Automation Engineers,…
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 and optimize AI/ML models using Python, TensorFlow, and PyTorch, focusing on RAG, LangChain, and locally run AI with Ollama for production deployment.
Designs the architecture for self-learning AI agents and GenAI systems, focusing on orchestration, reasoning layers, and scalable production pipelines.
Build and deploy ML pipelines and LLM services for a healthcare AI platform that supports population health and clinical decision-making.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to improve search, recommendations, and automation.
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