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Leads the conversational core of ServiceNow’s Voice AI platform, focusing on dialog quality, LLM selection, and customer enablement for enterprise voice agents. Owns product roadmap, scaling from early adopters to 100+ customers annually while competing with startups and CCaaS incumbents.
Concevoir et optimiser des modèles de langage (LLM) pour des cas d’usage métiers et automatiser des processus complexes dans l’aéronautique et la défense.
Build full-stack AI-powered apps for enterprise clients using JavaScript, Node.js, Vue/React, and PostgreSQL, shipping features from idea to production in a fast-moving startup.
Design and deploy enterprise-grade data pipelines and generative AI solutions on Azure, integrating Azure OpenAI and RAG to enhance investment decision-making and operational efficiency.
Solutions Engineer at Glean, a Work AI platform, demos and integrates AI-powered search and agents for enterprises, translating tech into business outcomes.
Builds and maintains scalable AI/ML data pipelines, integrates diverse data sources, and collaborates with ML teams to deploy models using Terraform/Terragrunt in an Agile environment.
Lenovo is seeking a Finance AI Full Stack Engineer to design and deploy enterprise-grade AI solutions using LLMs, RAG, and multi-agent systems. The role involves building end-to-end applications, integrating with ERP systems, and optimizing AI performance for finance-related workflows.
Develop and optimize enterprise applications focused on product security, debugging, and performance tuning for AMD’s global IT and supply chain systems using Java, C++, Python, and SQL.
Design and build data systems for pandemic therapeutics research, integrating biological and clinical datasets with AI tools at the Doherty Institute.
Build and orchestrate autonomous AI agents in Azure and Claude to automate software pipelines and deliver enterprise-grade AI-native solutions.
Build and deploy AI models end-to-end, from data pipelines to production, using Python and frameworks like TensorFlow or PyTorch.
Build and maintain cloud data pipelines in Snowflake and Databricks, ensuring clean, governed data for analytics and AI features while collaborating with data scientists and BI teams.
Leads AI-driven full-stack development, architecting backend systems in Node.js and frontend with React/Next.js, integrating AI capabilities into product pipelines while guiding a cross-functional engineering team.
Lead AI-driven full-stack development for a product company, owning backend (Node.js, Python), frontend (React/Next.js), and AI integrations (LLMs, RAG pipelines). Architect scalable systems, mentor engineers, and champion AI coding tools.
Owns and automates on-premises infrastructure, including GPU servers for AI/ML, while building secure CI/CD pipelines and observability stacks for local production systems.
Builds and maintains on-premises ICT infrastructure and GPU-enabled AI/ML compute, handling server lifecycle, automation, and Kubernetes clusters in a hands-on DevOps role.
Builds and maintains data pipelines on Databricks, integrates and cleans data from various sources, and collaborates with teams to ensure data quality and performance.
This role is for a Product Engineer at a fast-growing AI startup in London, where you will own features end-to-end and solve complex technical challenges at scale.
Designs and implements scalable cloud infrastructure and CI/CD pipelines using Kubernetes, OpenShift, and monitoring tools to ensure reliable deployments for an AI-driven governance tool company.
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