AI Engineer / Data Engineer - Agentic AI

Thales
Quebec City
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: bachelorsSkills: ["Autonomy","Curiosity","Communication"]

Design and build agentic AI and GenAI-enabled data platforms and applications that integrate LLM-based architectures. Own ingestion, ETL, transformation, synchronization, and data pipelines that feed RAG systems, vector stores, and knowledge bases. Develop agent workflows (e.g., LangGraph/LangChain/Semantic Kernel/AutoGen/CrewAI), connectors to enterprise systems, and observability for monitoring and evaluation. Partner with Data Science, MLOps, software development, and architecture to deploy mission-critical solutions in production.

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FursaFursa
Thales
Thales
3 days ago

AI Engineer / Data Engineer - Agentic AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Design and build agentic AI and GenAI-enabled data platforms and applications that integrate LLM-based architectures. Own ingestion, ETL, transformation, synchronization, and data pipelines that feed RAG systems, vector stores, and knowledge bases. Develop agent workflows (e.g., LangGraph/LangChain/Semantic Kernel/AutoGen/CrewAI), connectors to enterprise systems, and observability for monitoring and evaluation. Partner with Data Science, MLOps, software development, and architecture to deploy mission-critical solutions in production.
Location: Quebec City
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and implement large-scale AI models to solve complex problems.
  • •Build and integrate agentic AI workflows (e.g., MCP/agent tools/servers) with GenAI and LLM-based architectures.
  • •Develop and maintain ETL/data pipelines, transformations, and synchronizations to support agent inputs/outputs.
  • •Develop RAG-related data architectures, knowledge bases, vector stores, and indexing mechanisms for agents.
  • •Ensure data quality, governance, security, traceability, and provide observability/monitoring/evaluation for agent performance.

Key Requirements

  • •3+ years of experience in Data Engineering or developing data platforms.
  • •1+ years of experience in generative AI, RAG solutions, or LLM-based architectures.
  • •Demonstrated experience putting large-scale AI solutions into production.
  • •Hands-on with Python and SQL/data modeling.
  • •Experience with modern data platforms and data integration/orchestration tools (e.g., Databricks, Snowflake, Fabric, BigQuery, Redshift; Airflow, Data Factory, Dagster, Prefect).
Experience:3+ years
Education:Bachelor's
Skills:AutonomyCuriosityCommunication
Certifications:AzureAWSGCP
Languages:FrenchEnglish
Tech Stack:PythonSQLDatabricksSnowflakeFabricBigQueryRedshiftAirflowData FactoryDagsterPrefectLangGraphLangChainSemantic KernelAutoGenCrewAIAzure AI SearchPineconeWeaviateChroma

Company Brief

Thales
Designs and delivers advanced systems and services for aerospace, defence, security, and digital identity and cybersecurity markets, serving government and commercial customers worldwide.
Industry: Defense Technology
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Paris, France
Founded: 2000
WebsiteLinkedIn