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Lead AI product engineering for generative AI models at a large healthcare company, developing and deploying novel AI features.
Embeds with enterprise clients to design and ship production-grade Python and GenAI systems (RAG, agents) using AWS, while owning architecture, client communication, and delivery from discovery to deployment.
Designs, builds, and deploys production-ready Generative AI solutions using LLMs and RAG systems to enhance business outcomes.
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.
Designs and builds AI-powered legal workflows and products by translating legal expertise into structured processes and KI specifications, collaborating with engineers and lawyers to automate and enhance legal services.
Build production-grade generative AI systems for legal use cases using LLMs, RAG, and agentic workflows while ensuring reliability, security, and compliance.
Develops and deploys advanced AI agents at the intersection of research and engineering, focusing on Agentic RAG, context management, and multi-agent systems for real-world task execution.
Lead AI/ML projects for clients, designing and deploying agentic systems, ML models, and cloud-native solutions while advising on technical architecture and delivery at scale.
Leads AI and technology consulting engagements for enterprise clients, designing and delivering scalable AI/ML solutions while managing teams and client relationships in sectors like energy, financial services, and government.
Builds and optimizes AI training pipelines, annotation workflows, and model evaluation tools to improve machine learning performance at scale, collaborating with data scientists and researchers.
Designs, codes, and deploys scalable GenAI services, chatbots, and autonomous agents using modern frameworks; maintains LLM infra on-premise (Docker/Kubernetes), optimizes RAG pipelines, and ensures security. Core tech: Python, LLMs, RAG, vector databases, Docker/Kubernetes.
Senior AI Engineer at Ramboll3 in Aarhus, Denmark will shape the company's AI practice across products, focusing on ML/LLM engineering methods, standards, and practices. The role involves establishing evaluation practices, MLOps foundations, building production-grade LLM features, mentoring, and ensuring responsible AI usage with core technologies including Python, LLMs, and on-prem GPU infrastruc
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major…
Design and build GenAI agents that assist Bosch engineers with tasks like requirements analysis, documentation, and failure analysis using LLMs, embeddings, and vector databases.
Leads a team of Google Cloud Solution Architects to co-create production-scale MVPs with strategic customers, blending business strategy with advanced engineering (AI, data, security, software) to drive digital transformation and unblock technical deployments.
Senior Full Stack Engineer with a focus on data infrastructure, designing and owning end-to-end data pipelines, storage, and retrieval systems while contributing to broader product architecture and AI-ready system design.
Build and deploy AI-powered automation workflows using Python/Node.js, n8n/Zapier/Make, and LLMs (Claude/Gemini/OpenAI) to streamline business processes and enable teams to self-manage solutions.
Embedded engineering manager who codes, deploys, and scales bespoke GenAI solutions for strategic partners, bridging AI prototypes to production-grade systems while feeding partner insights into Google Cloud’s AI roadmap.
Builds and scales Kubernetes-based AI infrastructure for a legal LLM platform, handling GPU workloads, CI/CD pipelines, and high-load monitoring to support real-time inference and integrations.
Build and operate scalable backend services that power AI-driven workforce management features using Java, Python, and cloud-native tools.
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