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Builds and integrates AI features into product workflows, turning model capabilities into real-world automation and user-facing decisions within insurance processes.
Build and ship an AI agent that automates car-rental sales and support: design prompts, integrate with CRM, and tune conversational flows to handle bookings, extensions, and FAQs.
Build and deploy AI agents and RAG systems using TypeScript/Node.js and React, integrating LLM APIs with tool use and structured outputs.
Design and deploy production-grade GenAI and ML solutions on AWS, optimizing cost, security, and performance while embedding reusable patterns into DoiT’s Cloud Intelligence platform.
Build and validate AI agents and DevOps workflows to automate system validation, debugging, and optimization for AMD’s hardware platforms.
Senior AI Engineer building GenAI applications with LLMs, RAG, agents, and semantic search in Python, integrating models via APIs and deploying backend services.
Build and deploy production-grade AI systems, including RAG pipelines, agentic workflows, and scalable APIs with Python and cloud-native tools.
Build and deploy AI-powered cybersecurity agents that autonomously investigate threats using LLMs, tool-calling workflows, and evaluation frameworks.
Build and industrialize AI/ML pipelines for Crédit Agricole, turning experiments into secure, scalable production systems using MLOps, LLMOps, and data engineering.
Designs and builds cloud data pipelines on AWS, integrates data lakes and Snowflake, and deploys generative AI and Agentic AI solutions for an industrial high-tech group.
Design and build ML use cases and data pipelines on Google Cloud Platform using BigQuery and Python.
Build AI-powered data visualization features for Datadog’s dashboards and investigations, blending LLM-driven insights with reliable, scalable systems.
Build and deploy AI agents and GenAI tools to automate parts of the software development lifecycle, integrating them with existing systems on Google Cloud Platform.
Design and build data pipelines to transform raw data into insights using cloud tools and ETL processes for a global healthcare company.
Builds and optimizes big-data pipelines and ML/LLM infrastructure to support strategic decision-making and AI-driven analytics.
Data & AI Engineer builds and deploys insurance-focused AI use cases, from data exploration to production, with strong data workflow and cybersecurity elements.
Build and maintain AI-ready data pipelines and platforms to accelerate drug discovery and development in a hybrid R&D team.
Build and maintain Snowflake-based data pipelines and AI platforms for clients, using Python, Spark, Airflow and Kubernetes to turn raw data into business insights.
Build and deploy AI agent applications in Python/JavaScript, integrating them with existing systems and Google Cloud Platform while using generative AI tools to accelerate the software development lifecycle.
Lead the design and delivery of data pipelines and AI workflows for healthcare solutions using tools like Snowflake, Airflow, and Python.
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