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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 fine-tune AI models using Python, TensorFlow/PyTorch, and cloud services like AWS Bedrock and Azure OpenAI to deliver industry-specific solutions.
Builds AI-powered websites, chatbots, and voice agents for UK clients by engineering prompts, integrating APIs, and automating workflows using modern AI platforms.
Designs the architecture for self-learning AI agents and GenAI systems, focusing on orchestration, reasoning layers, and scalable production pipelines.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to improve search, recommendations, and automation.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to automate workflows and improve user experience.
Build backend services integrating AI APIs and trading systems using Python, FastAPI, and SQL.
Build and ship AI-powered agentic applications using Python, LangChain/LangGraph, and vector databases; lead system design, DevOps, and team mentorship.
Build production-grade AI agents and LLM-powered features like chatbots and RAG systems using Python, FastAPI, and third-party models (OpenAI, Gemini, Claude).
Build and deploy production AI systems, including LLM-powered chatbots and RAG pipelines, using Python/Node.js and cloud infrastructure.
Build AI-powered learning features using RAG and MCP, optimize performance for global users, and manage SQL/MongoDB systems with React/TypeScript and Python/Node.js.
Build and optimize AI-powered features, performance-tune React/TypeScript frontends, and manage SQL/MongoDB data systems for a global social learning platform.
Build and scale a high-volume real-time communications platform with AI-driven automation using Node.js, Python, Vue/React, and cloud services.
Builds enterprise-grade Python/Django and FastAPI backends plus React/Next.js frontends, deploys on AWS, and integrates AI models (OpenAI, LangChain) into scalable microservices.
Build AI-assisted backend systems for cloud storage, focusing on APIs, data pipelines, and AI workflows using Python, Go, and AI coding tools.
Build and maintain AI-ready data pipelines and retrieval infrastructure for a fintech SaaS, using AWS, TypeScript, Python, and vector search to power RAG and agent systems.
Build and scale Airweave’s distributed data pipelines, vector databases, and LLM inference infrastructure to power thousands of AI agents reliably at scale.
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