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Build and lead generative AI and data-science solutions, designing multi-agent patterns, tooling, and MLOps pipelines in Python/Java with cloud providers.
Designs AI solutions for clients, creating blueprints, estimates, and delivery plans while partnering with cross-functional teams to align technical, commercial, and operational needs.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines.
Leads the design and deployment of production-grade AI systems, including multi-agent workflows and RAG architectures, using GCP and MLOps/LLMOps pipelines to scale genAI across global operations.
L’IA chez Smile, ce n’est pas un buzzword : c’est une pratique. Des modèles et des cas d’usage ouverts, performants et durables, pensés pour passer en production — pas des PoC qui finissent au tiroir. On bâtit sur des…
Build and maintain an NLP/LLM pipeline that extracts entities from financial news and disclosures, links them to a financial ontology, and powers RAG/Graph RAG features for evidence-backed answers in a securities trading platform.
Designs and builds generative AI systems using LLMs, agentic architectures, and RAG pipelines, then deploys and monitors them in production.
Lead enterprise AI/ML and generative AI initiatives, designing and deploying LLM-based solutions, setting strategic roadmaps, and mentoring teams to drive scalable, secure AI adoption in a large financial services firm.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Build and maintain Tangerine’s AI/ML platform, including MLOps, RAG pipelines, and agentic systems, to power next-gen banking features and client experiences.
Lead a small team to design, build, and deploy production-grade generative AI systems using Python, RAG pipelines, vector databases, and cloud platforms while mentoring engineers and aligning solutions with business goals.
Design and build secure, compliant AI/ML platforms on AWS and Azure for a large bank, including MLOps pipelines, guardrails, and observability for regulated environments.
Build and deploy generative AI models (LLMs, RAG, prompt engineering) on Azure to solve fintech problems like health analytics and operations modernization.
Leads architecture and delivery of enterprise-scale GenAI and agentic AI systems on GCP for travel retailing, including RAG, agent workflows, and LLMOps pipelines.
Lead presales architecture for enterprise data, AI, and application modernization deals, designing integrated solutions and guiding clients through cloud-native transformations.
Designs, builds, and deploys production-grade AI agents, copilots, and intelligent automations to transform business processes using enterprise AI platforms and low-code/no-code tools.
Build and operate HERE’s enterprise AI Hub: shared runtime, CI/CD, model registry, and observability for scalable, secure AI deployments and intelligent agents.
Build and deploy generative AI systems, RAG pipelines, and multi-agent workflows using LLMs (OpenAI, Azure OpenAI, open-source) and MLOps/LLMOps practices.
Lead DevOps Engineer designs and maintains CI/CD pipelines, infrastructure-as-code, and cloud-native architectures using Azure DevOps, Bicep, and Azure services.
Embed within client teams to design and deploy scalable data platforms, ML pipelines, and GenAI workflows using Python, Spark, and cloud-native tools.
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