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Lead a team building production-grade GenAI and multi-agent AI systems for a major bank, owning architecture, prototyping, evaluation and deployment to deliver measurable customer and business outcomes.
Build and deploy enterprise-grade AI agents and multi-agent systems using Python, LangChain/LangGraph, and RAG architectures for scalable copilots and automation.
Build and deploy production-grade agentic AI and LLM applications for APAC enterprises, including RAG pipelines, multi-agent systems, and ML services across cloud and air-gapped environments.
Build and scale AI-driven features for iGaming, including generative AI, voice AI, agentic systems, and RAG pipelines using Python, LLMs, and cloud infrastructure.
Build and deploy production-grade AI systems, including LLMs, Generative AI, and Agentic AI, while establishing MLOps/LLMOps pipelines and responsible AI practices.
Build and maintain full-stack web apps in TypeScript/Java/Node.js with AI integrations using LLMs, RAG, and vector databases to modernize lending workflows.
Drive the future of Agentic AI at Pearson as part of the 'AgentOps' team. Inspire innovation. Empower learning. Why Join AgentOps Work on cutting-edge agentic AI systems at enterprise scale Help build a…
Design and govern enterprise AI solutions (e.g., Claude Enterprise) that drive measurable business outcomes across healthcare operations, ensuring security, compliance, and scalable adoption.
Principal AI Solution Architect designs and scales enterprise-grade generative and agentic AI systems, leading PoCs, architecture reviews, and responsible AI governance for clients across industries.
Designs enterprise AI architectures, governance frameworks, and scalable solutions using LLMs, RAG, and AI agents while aligning with business goals and security standards.
Build and deploy AI features for banking platforms, leading from prototype to production while ensuring regulatory compliance and cross-team adoption.
About the Role We're an early-stage open-source MLOps infrastructure startup building the orchestration layer for ML pipelines and AI agent workflows. We're looking for a GTM Engineer to own our entire US…
Architects AI/GenAI product portfolios, defining target architectures, MLOps/LLMOps pipelines, and retrieval systems while ensuring Responsible AI and cost-efficient inference at scale.
Designs and owns production-ready AI and GenAI solutions, including LLMs, RAG, agentic systems, and MLOps/LLMOps pipelines, ensuring reliability, safety, and cost efficiency.
Lead the architecture and delivery of enterprise AI systems using LLMs, RAG, and AI agents, setting engineering standards and mentoring teams to build secure, scalable, and responsible AI solutions.
Build and deploy generative AI models (LLMs, multimodal) using Azure Databricks, Hugging Face, and LangChain for content personalization, automation, and semantic analysis.
Build enterprise GenAI applications using LLMs, RAG, and agentic workflows with Python, LangGraph, and cloud tools in a hybrid role.
Design and implement scalable data architectures for AI systems, build robust pipelines, and lead MLOps/LLMOps deployments using Python, Spark, and cloud platforms.
Build and deploy ML/LLM-powered services for Workato’s iPaaS platform, shipping scalable AI features and improving model performance with Python and modern MLOps practices.
Design and build generative AI systems using LLMs, agentic architectures, and RAG pipelines, optimizing models and managing unstructured data for scalable production deployments.
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