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Designs and secures AI platforms, AI APIs, and AI-enabled applications while integrating security into CI/CD pipelines and cloud-native environments across Azure, AWS, and GCP.
Build and maintain the infrastructure that trains, deploys, and serves AI models at scale, using Python, PyTorch/JAX, and LLM serving stacks like vLLM.
Build and ship LLM-powered AI agent workflows that orchestrate multi-step tasks, integrate tools, and turn probabilistic model outputs into reliable user experiences.
Build and ship LLM-powered AI agent workflows that orchestrate multi-step reasoning, tool use, and real-world task completion with high reliability and user impact.
Build and maintain full-stack AI-native marketing platform using TypeScript, Python, and agentic coding tools like Claude Code; develop ML models, RAG pipelines, and LLM evaluation frameworks.
Build AI-powered CRM demos and prototypes using LLMs, Salesforce, and full-stack engineering to solve enterprise challenges and showcase solutions to clients.
Senior role building LLM features and retrieval-augmented generation systems to enhance property management solutions using Python, TypeScript, and vector search.
Build and deploy AI applications (e.g., conversational assistants, RAG systems) and data pipelines on cloud platforms, while ensuring compliance with government security standards.
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 deploy AI systems, including LLM-based agents and retrieval workflows, using Python and cloud-native stacks to power healthcare products and enterprise solutions.
Designs enterprise-scale AI architectures for healthcare, including generative AI apps, agentic systems, and LLM-powered workflows, while ensuring security, compliance, and cloud-native integration.
Build and optimize LLM-powered AI assistants for a bank’s internal support systems using Python, RAG, and vector databases.
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.
Build and deploy production-grade GenAI applications for enterprise clients, integrating LLMs, RAG, and agentic workflows with Python and modern AI frameworks.
Architects advanced healthcare-focused AI systems using LLMs, RAG, and tool-calling patterns to deploy safe, reliable conversational agents at scale.
Design and deploy advanced healthcare-focused AI systems using RAG, tool-calling, and LLM techniques; architect production-grade AI agents for clinical environments.
Build .NET backend services and APIs for a hospitality platform, integrating with Android apps, hotel systems, and AI tools to power digital guest experiences like check-in, mobile keys, and interactive TV.
Job Summary: We are looking for a Senior AI Engineer to design and build production-grade Agentic AI and LLM-powered systems . The ideal candidate is a strong Python engineer with hands-on experience in RAG,…
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