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Build and maintain a universal data platform that integrates enterprise data sources into automated pipelines, ensuring high-quality data for AI agents, LLMs, and RAG workflows using Python, SQL, and GCP services.
Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and scale Snowflake-based data and AI systems, designing pipelines, models, and LLM/RAG applications that turn messy business data into trusted, production-ready solutions.
Build and maintain a production platform that collects, processes, and enriches social media content using Python, ETL pipelines, and LLM APIs for classification and summarization.
Build and deploy ML models and AI solutions for global clients, from LLMs to optimization engines, using Python, cloud platforms, and MLOps practices.
Lead the design and deployment of AI/ML systems for global clients, including optimization engines and LLM-powered recommendation systems using Python, AWS, and MLOps practices.
Build and deploy ML models and AI systems for enterprise clients, focusing on LLMs, NLP, and computer vision to solve industrial, automotive, and software-engineering challenges.
Build and deploy AI-powered safety systems: liveness detection, fraud/abuse detection, audio analysis, and safety scoring using CV, NLP, and LLM pipelines in a high-load production environment.
Build and maintain production-grade AI systems for document processing and retrieval-augmented generation in a global marketing-tech stack.
Build and maintain AI-powered search infrastructure: ETL pipelines, embedding generation, document processing, and ranking systems to power semantic search and AI agent queries.
Build and maintain AI-powered search infrastructure: ETL pipelines, semantic embeddings, document processing, and retrieval systems to power accurate AI responses.
Build and operate Snowflake-based data platforms that power GenAI and advanced AI use cases at enterprise scale, integrating vector search, RAG, and agent workflows.
Build and curate insurance data assets, integrate GenAI for data quality, and deliver Power BI dashboards to support underwriting and claims decisions.
Build and evolve Roche’s internal AI Agentic Platform, designing scalable agentic workflows, reusable components, and enterprise integrations for secure, compliant AI solutions in healthcare.
Lead AI systems design for Thomson Reuters’ Audit Suite, building scalable backend orchestration for generative AI agents, retrieval workflows, and MCP servers in C#/.NET and Python.
Architect and deliver production-grade AI systems, including agentic workflows and RAG pipelines, using Python, LangChain, and AWS Bedrock. Work with clients to embed AI into enterprise processes and scale intelligent solutions.
Build and maintain AI-powered data pipelines, GenAI features, and full-stack apps for an Italian enterprise client using Python, cloud services, and modern JS frameworks.
Build and deploy agentic AI systems for clients, designing multi-agent workflows, RAG pipelines, and tool-using LLMs with AWS Bedrock and LangChain, while owning end-to-end delivery from architecture to production.
Lead AI-powered features for an enterprise document-management platform, defining strategy for generative AI, semantic search, and intelligent metadata while collaborating with engineering and marketing teams.
Design and productionize enterprise AI solutions using Snowflake Cortex AI, Python, SQL, and RAG architectures to automate decisions and build intelligent agents for Hydro One’s data platform.
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