AI Engineer / Data Engineer - Agentic AI

AI Engineer / Data Engineer - Agentic AI

Quebec City, QC (Hybrid) Full-time

Job Summary

The Thales Group is a global organization present on all continents, serving five major markets, all of vital importance to our societies: aerospace, space, defense and security, and digital identity and security. From the ocean floor to the depths of space and cyberspace, the Thales Group offers a unique range of technologies and services that make tomorrow possible, today. Whether helping cities and critical infrastructure become safe and smart, securing global financial markets, protecting data and privacy, and keeping security forces connected during critical missions, Thales ensures that everyone can continue to share information and enjoy the benefits of a connected world and enjoy a better quality of life, while remaining safe and staying one step ahead of all forms of digital threat.

Our team conducts research and development (R&D) work to meet the needs of the Department of National Defence (DND) and the Canadian Armed Forces (CAF). The projects focus on innovative digital solutions combining software development, systems integration, modern infrastructure, and generative artificial intelligence.

As part of accelerating our artificial intelligence initiatives, we want to develop a new generation of applications based on Agentic AI. These solutions go beyond traditional conversational assistants by allowing intelligent agents to analyze data, reason, make decisions, orchestrate complex workflows, and interact with multiple enterprise systems autonomously and securely.

We are looking for a Data Engineer specializing in generative AI and Agentic AI to join our team in Quebec City, specializing in knowledge management. Our multidisciplinary team focuses on data collection, transformation, and enrichment. Our projects involve defining and deploying automated processing pipelines to make data accessible to users. With the support of our data scientists, the team designs, trains, and integrates artificial intelligence models, including generative AI (GenAI) based on Large Language Models (LLMs), to improve data analysis. Our team also uses AI and machine learning (ML) concepts to increase analysis efficiency.

Essential Functions

The Data Engineer specialized in generative AI and Agentic AI will play a key role in the design, development, and deployment into production of intelligent platforms and applications integrating language models (LLMs), agentic architectures, ingestion and transformation pipelines, data tools and servers such as MCP or others, orchestration tools, and next-generation cloud services. This person will contribute to strategic projects aimed at improving operational efficiency, human decision support, and the automation of complex processes in environments where security, reliability, and traceability are essential. This person must be autonomous, curious, and comfortable in an R&D context where needs evolve rapidly. Being able to understand the reality of users and data, as reported by the PO and challenging technical options, helping the architect make informed decisions by finding and testing approaches found on the web or vibe-coded quickly. The person must be able to work, as applicable, both in a rapid and agile mode, and in a production mode with rigor by applying engineering, development, and testing practices and security rules according to the application context. They will work with architects, developers, and artificial intelligence specialists to transform technical concepts into concrete, demonstrable, and scalable solutions.

This person is part of a multidisciplinary team. A strong team spirit and teamwork capabilities are mandatory. The ideal candidate is therefore able to demonstrate cross-functional skills that would facilitate the transfer of work done to all stakeholders involved. Therefore, good communication skills are required.

Responsibilities of the Data Engineer in Agentic AI:

• Design and implement large-scale AI models to solve a wide variety of complex problems.
• Participate in the integration of generative AI solutions for agentic workflows, creation of agent tools or MCP servers or MCP Apps.
• Participate in the development and maintenance of data sources exploited by agents (input or output), by creating ETL pipelines, transformation, synchronization between various formats, sources, and distributed systems.
• Demonstrate good judgment in the choice of methods and techniques to obtain solutions.
• Design, develop, and maintain the data pipelines necessary to feed generative AI systems and autonomous agents.
• Develop and optimize data architectures allowing for Retrieval-Augmented Generation (RAG).
• Design and manage knowledge bases, vector stores, and indexing mechanisms for AI agents.
• Build and integrate agent workflows using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or CrewAI.
• Develop connectors allowing agents to interact with enterprise systems (ERP, CRM, databases, APIs, collaborative platforms).
• Ensure quality, governance, security, and traceability of data used by AI agents.
• Set up mechanisms for observability, monitoring, and performance evaluation of agents.
• Collaborate with Data Science, MLOps, Software Development, and Architecture teams in order to deploy AI solutions in production.
• Design and implement context management, memory, and knowledge strategies for agents.
• Optimize costs, latency, and performance of solutions based on LLMs.
• Participate in the evaluation and integration of new foundation models.
• Automate deployment, testing, and maintenance of Agentic AI components.
• Define and apply best practices in responsible AI, security, and compliance.
• Perform proofs of concept and support the industrialization of new Agentic AI capabilities.

Minimum Requirements

• Master's or Bachelor's degree in computer science, engineering, information technology, or any other related and relevant field.
• 3+ years of experience in Data Engineering or data platform development.
• 1+ years of experience in generative AI, RAG solutions, or LLM-based architectures.
• Demonstrated experience in deploying large-scale AI solutions into production.
• Experience with the integration of complex enterprise systems and APIs.
• Experience in modern cloud environments.
• Experience in solution architecture and collaboration with multidisciplinary teams.
• Good command of Python.
• Experience in SQL and data modeling.
• Experience with modern data platforms (Databricks, Snowflake, Fabric, BigQuery, or Redshift).
• Experience and mastery of data transformation tools and platforms and connectors between formats/systems for ETL, Sync, or augmentation.
• Experience with data integration pipelines and orchestration (Airflow, Data Factory, Dagster, Prefect).
• Hands-on experience with LLMs and Agentic APIs.
• Mastery of at least one LLM or Agentic AI framework: LangGraph, LangChain, Semantic Kernel, AutoGen, or CrewAI.
• Experience with vector databases (Azure AI Search, Pinecone, Weaviate, Chroma, Qdrant, Elasticsearch).
• Understanding of prompting, tool calling, function calling, and multi-agent orchestration mechanisms.
• Knowledge of evaluation techniques for generative systems and autonomous agents.
• Experience with Azure, AWS, or GCP.
• Knowledge of Docker containers and Kubernetes.
• Mastery of CI/CD practices.
• Experience with Infrastructure as Code (Terraform, Bicep, or CloudFormation).
• Experience in observability and monitoring (Prometheus, Grafana, OpenTelemetry).
• Fluency in French (spoken and written).

Desirable Qualifications

• 5+ years of experience in Data Engineering or data platform development.
• 2+ years of experience in generative AI, RAG solutions, or LLM-based architectures.
• Experience with Microsoft Fabric and Azure AI Foundry.
• Experience with Semantic Kernel and the Microsoft Copilot ecosystem.
• Knowledge of fine-tuning, distillation, and model evaluation techniques.
• Open source contributions in Data Engineering or AI fields.
• Knowledge of Lakehouse and Data Mesh architectures.
• Experience with cloud AI platforms (Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI).
• Azure, AWS, or GCP certifications.
• Experience in regulated environments (finance, insurance, health, public sector).
• Knowledge of the defense domain, military intelligence, or Canadian Armed Forces context.
• Fluency in English (spoken and written).

This position requires a good knowledge of English to interact, support, and/or provide services to international clients, employees, and/or partners as well as foreign government authorities who do not speak French.

Physical Requirements

This position may require the employee to set up equipment and conduct field experiments in an outdoor environment.

Thales provides an extensive benefits program for all full-time employees working 24 or more hours per week and their eligible dependents, including the following:

• Company paid Extended Health, Dental, HSA, Life, AD&D, Short-term Disability, travel insurance, Employee Assistance Plan and Well-Being program.
• Retirement Savings Plans (RRSP, DCPP, TFSA) with a company contribution and a match to a DCPP, with no vesting period.
• Company paid holidays, vacation days, and paid sick leave.
• Voluntary Life, AD&D, Critical Illness, Long-Term Disability.
• Employee Discounts on insurance (home, and auto).

Thales is an equal opportunity employer which values diversity and inclusivity in the workplace. Thales is committed to providing accommodations in all parts of the interview process. Applicants selected for an interview who require accommodation are asked to advise accordingly upon the invitation for an interview. We will work with you to meet your needs. All accommodation information provided will be treated as confidential and used only for the purpose of providing an accessible candidate experience.

This position requires direct or indirect access to hardware, software or technical information controlled under the Canadian Export Control List, the Canadian Industrial Security Program, and/or the US Export Administration Regulations (EAR). All applicants must be eligible or able to obtain authorization including a Canadian Enhanced Reliability security clearance.