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Location: Quebec City, Canada Dans des marchés en rapide évolution, les clients à travers le monde font confiance à Thales. Thales est une entreprise où les personnes les plus brillantes du monde entier se regroupent…
Forward Deployed Engineer embedding with client teams to deploy, integrate, and scale enterprise Generative AI solutions on Google Cloud Platform, working with LLMs, vector databases, RAG pipelines, and GKE infrastructure.
Senior forward-deployed engineer embedded with Carlyle's Finance and Fund Management teams, building full-stack AI/automation solutions for Global Wealth operational processes (NAV reporting, fee models) using AWS services, LLM/RAG architectures, and modern frontend/backend frameworks.
Sr. Technical Analyst for Agentic AI at Johnson & Johnson, designing and delivering autonomous document-generation and cognitive-search platforms using agentic AI systems, LLMs, RAG, and orchestration frameworks like LangGraph.
Lead the product backlog and delivery of agentic AI document-generation and cognitive-search platforms at J&J MedTech, working with LLMs, RAG pipelines, multi-agent frameworks (LangGraph, CrewAI, AutoGen), vector databases, and AWS AI services.
Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data Building and operating APIs, backend services, and pipelines to keep data current and accessible…
Forward Deployed Engineer embedded with biopharma customers to design, build, and ship AI-powered production systems (Python/Django, AWS Bedrock, PostgreSQL) directly into Condor's core platform, solving clinical operations and financial workflow problems.
Senior Software Engineer building AI-powered internal tools (code assistants, search, chat) to boost developer productivity at Instacart, using Python/Go/Java, LLMs, and cloud infrastructure.
This FullStack Developer role involves building end-to-end enterprise applications using Angular, Java/Spring Boot, and Generative AI technologies. The developer will integrate LLMs, build RAG solutions, and implement intelligent agents within cloud-based microservices architectures.
Build and maintain the data foundations for a legal AI platform, modeling product analytics, KPIs, and dashboards using BigQuery, dbt, and Python.
Builds and deploys AI-driven mental health support systems, focusing on LLM safety, guardrails, and ethical design for a global crisis support platform.
Senior Fullstack Developer building a generative AI platform for orchestrating agents, flows, and models using Node.js, Python, LangChain, CrewAI, React, and vector databases in a fully remote role.
Builds and deploys GenAI applications (LLM-based assistants, search engines, automation tools) by designing RAG pipelines, integrating cloud AI models, and ensuring scalability, security, and performance for enterprise clients.
Senior Data Engineer developing and maintaining a data warehouse platform using Scala, Rust, and Python, with Kubernetes/Docker-based DevOps tooling and LLM inference technologies (vLLM, TensorRT-LLM, Triton).
Senior AI Engineer builds secure RAG/LLM systems and NLP pipelines for defense intel, integrating legacy data and ensuring DoD compliance.
This early-career role involves designing and deploying AI-powered applications and cloud-native solutions for federal clients using AWS and Azure. The engineer will work with senior staff on RAG workflows, AI agents, and infrastructure automation while supporting digital transformation initiatives.
Lead the end-to-end development of client-facing GenAI web applications in Brussels, integrating LLMs and orchestrating AI logic using Python and Next.js.
Senior AI Engineer/Technical Consultant designs and delivers AI solutions for clients, leading from architecture to production using Python, LLMs, and cloud platforms like Azure/GCP/AWS.
This role involves building and maintaining the data platform and backend services that power AI features for an educational platform. You will design data models, manage ingestion pipelines, and ensure system reliability in a production environment using Python, SQL, and AWS.
Design and operate the data platform behind Instructure's AI features—data models, pipelines, and backend services using Python, SQL, AWS, and relational/graph databases.
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