AI Engineer / Data Engineer - Agentic AI

AI Engineer / Data Engineer - Agentic AI

Quebec City, QC (Hybrid) Full time

Role 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 bottom of the oceans 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 mission-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 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 in an autonomous and secure manner.

We are looking for a Data Engineer specialized in generative AI and Agentic AI to join our team in Quebec, specializing in knowledge management. Our multidisciplinary team focuses on data collection, transformation and enrichment. Our projects involve the definition and deployment of automated processing chains 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 production deployment 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. The person holding this position 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 challenge technical options, help the architect make informed decisions and by finding and testing quickly approaches found on the web or vibe coded. The person must be capable of working, depending on the case, both in fast and agile mode, and in 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 skills are mandatory. The ideal candidate is therefore able to demonstrate transversal skills that would facilitate the transfer of work done to all stakeholders involved. Therefore, good communication skills are required.

Responsibilities of the Agentic AI Data Engineer:

• 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.
• Exercise discernment 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.
• Implement observability, monitoring and performance evaluation mechanisms for agents.
• Collaborate with Data Science, MLOps, Software Development and Architecture teams 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.
• Carry out 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 architectures based on LLMs.
• Demonstrated experience in putting 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).
• Practical 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 mechanisms, tool calling, function calling and multi-agent orchestration.
• 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).
• Mastery of 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 architectures based on LLMs.
• 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, healthcare, public sector).
• Knowledge of the defense, military intelligence or Canadian Armed Forces context.
• Mastery of 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 to 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.

About Thales

In a world that is increasingly fast moving, unpredictable – and full of opportunities, trust is essential for societies to flourish. Trust in our institutions. Trust in our systems. Trust in technology. Trust in each other.

And the people we all rely on to make the world go round, they rely on Thales. They come to us with big ambitions: to make life better, to keep us safer.

From the bottom of the oceans to the depths of space and cyberspace, we help our customers navigate uncertainty with confidence and new frontiers with optimism. Thinking smarter and acting faster - mastering ever greater complexity and every decisive moment along the way.

We collaborate to architect and deliver high technology solutions that are both imaginative and resilient, human-centered and sustainable. So that together we can harness the extraordinary power of technology to build a future we can all trust.