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Build and optimize multi-agent LLM systems and RAG pipelines for city-scale digital services using Python, FastAPI, and async pipelines.
Senior AI Engineer building GenAI applications with LLMs, RAG, agents, and semantic search in Python, integrating models via APIs and deploying backend services.
Lead a team building and scaling Azure-based data pipelines and AI-ready data models for a large ecommerce retailer using PySpark, Databricks, and Data Factory.
Build and deploy production-grade AI systems, including RAG pipelines, agentic workflows, and scalable APIs with Python and cloud-native tools.
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
Design, build, and deploy AI/ML models and services, including generative AI and RAG systems, while ensuring responsible AI practices and robust MLOps pipelines.
Build and deploy AI-powered cybersecurity agents that autonomously investigate threats using LLMs, tool-calling workflows, and evaluation frameworks.
Build and maintain the AI platform infrastructure that powers Plum’s fintech app, using Python, FastAPI, and agentic frameworks on GCP.
Builds and operates AI-driven backend services using Python, LLMs, and cloud-native microservices to create intelligent data products and scalable inference pipelines.
Build and scale cloud-native Java microservices on AWS, using AI tools to improve code quality and delivery speed while collaborating with global clients.
Build and maintain AI agentic backend systems using Python, LangChain/LangGraph, and vector databases to power autonomous workflows and RAG pipelines for business intelligence.
Lead GenAI and voice/audio ML infrastructure at a healthcare SaaS company, designing scalable platforms so product teams can ship AI-powered features like Call Intelligence and AI Receptionist.
Build and maintain scalable data pipelines, vector stores, and LLM-driven BI systems using Python, Spark, and cloud ML services to power real-time AI applications.
Build AI-powered finance apps using React, Node.js, and TypeScript, integrating data platforms and cloud services to deliver analytics and decision-making tools for finance teams.
Build and industrialize AI/ML pipelines for Crédit Agricole, turning experiments into secure, scalable production systems using MLOps, LLMOps, and data engineering.
Builds Python back-end services and AI pipelines for an enterprise GenAI assistant using FastAPI/Flask, LangChain, and Google Vertex AI on GCP.
Build and deploy data pipelines, cloud data platforms, and ML systems for clients using Databricks, Spark, AWS, and MLOps tooling.
Build and deploy scalable generative-AI systems on GCP, integrating LLMs and RAG into Air Liquide’s products while ensuring performance, cost, and observability.
Build and deploy scalable generative-AI systems on GCP, integrating LLM APIs, RAG, and agent workflows while ensuring reliability, cost control, and observability for an industrial group.
Build and deploy scalable generative-AI systems for Air Liquide’s products, focusing on LLM pipelines, RAG, and agent workflows on GCP’s Vertex AI and Agent Space.
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