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Senior engineer maintaining and improving production AI platforms on Kubernetes across on-premise, AWS, and GCP, using MLOps and Python to ensure reliability and scalability.
Design and deliver cloud-native, AI-powered enterprise applications using .NET, Azure, and generative AI tools, leading full-stack development and customer engagements.
Build and deploy production-grade AI agent systems for media workflows, embedding with teams to design, implement, and maintain reliable tool-using agents using RAG and orchestration frameworks.
Build and test AI-driven tools for a news publisher, focusing on LLM agents, prompt engineering, and automation to improve journalism and commercial workflows.
Builds and deploys production-grade AI agent workflows (LangGraph, Temporal) for Acquia’s enterprise digital experience platform, focusing on scalability, observability, and RAG architectures while mentoring peers.
Build and ship production-grade agentic AI workflows using LangGraph, Temporal, and LangFuse to power Acquia’s AI-powered DXP for enterprise-scale digital experiences.
Leads AI/ML engineering teams to design and deploy production-grade AI solutions (LLMs, classical models, agent systems) for consulting clients, focusing on architecture, context engineering, and fine-tuning pipelines while supporting pre-sales and strategy.
Designs and builds AI applications using LLMs, RAG pipelines, and agentic workflows, integrating foundation models via Amazon Bedrock and optimizing retrieval systems with ASP.NET.
Build and deploy AI/ML models using Python, LLMs, and vector databases in a cloud environment for generative AI applications.
Build an AI-augmented Quality Engineering framework using Python, LLMs, and MLOps to enable intelligent test generation, self-healing automation, and governance-as-code.
Build and scale a high-traffic file-services platform using TypeScript, React, and AI-first tools, while leading architecture and engineering culture.
Principal AI Engineer designs and deploys production-grade AI automation systems for a clinical data intelligence platform, using LLM frameworks and agentic workflows to streamline enterprise processes.
Builds and scales Generative AI systems, including LLM applications and research agents, using Databricks and Azure while ensuring responsible AI practices in a hybrid Toronto role.
Why Keyrus, Why Now! Keyrus is an international group of 2,800 consultants and experts across 28 countries , built on a single conviction: AI does not transform businesses. Architected intelligence does. For more than…
Consults clients on AI-driven process transformations, designing and deploying generative AI solutions (LLMs, agents, RAG) to solve business challenges while collaborating with tech teams on cloud, DevOps, and system integrations.
Vs — R&D команда проекта GigaLegal в СБЕР, создающая решения в правовой сфере на основе LLM для автоматизации юридических процессов. Наша цель — трансформировать работу юристов, бизнеса и госструктур через:…
Lead AI product engineering for generative AI models at a large healthcare company, developing and deploying novel AI features.
A Full-stack Engineer at EverHelp builds end-to-end features for AI-powered customer service products, including frontend (React/Next.js), backend (Node.js/Python), and AI components like agents and RAG systems, while designing high-load scalable systems and maintaining code.
AI Engineer will own the analysis engine, evaluation framework, retrieval systems, and agentic architecture for RIVA, a product that analyzes businesses using language models. Core technologies include Python, FastAPI, PostgreSQL, LLM SDKs, LangChain, DSPy, and vector databases like pgvector or Qdrant.
Builds scalable AI backend infrastructure and APIs for healthcare virtual care systems, integrating LLMs (OpenAI, Google Gemini, Gemma/Llama) and clinical data standards (FHIR).
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