Applied AI Engineer

Giesecke+Devrient • Montreal, QC

2d

About The Position

Giesecke+Devrient is a globally leading SecurityTech company. We are seeking a technical and execution-focused Applied AI Engineer to join G+D’s new AI Hub. The ideal candidate will combine hands-on experience in Generative AI systems engineering with strong Python software engineering capabilities and the ability to translate enterprise challenges into practical AI solutions that deliver measurable impact. This role is focused on Generative AI engineering and agentic systems, including single-agent and multi-agent architectures, RAG, Graph RAG, evaluation frameworks, guardrails, and production observability.

Requirements

• Two (2)+ years of hands-on experience in Generative AI engineering, LLM systems, or Applied AI, with experience building GenAI solutions.
• Three (3)+ years of experience in Python software engineering, backend engineering, platform engineering, or related software development roles.
• Experience building and deploying software systems, APIs, workflow orchestration services, or distributed applications.
• Strong practical knowledge of LLM systems, prompt engineering, RAG, agent orchestration, observability, hallucination mitigation, and MCP.
• Strong Python software engineering skills.
• Hands-on experience with Python, FastAPI / Flask, async workflows, APIs, testing frameworks, and CI/CD.
• Hands-on experience with tools such as LangChain, LangGraph, CrewAI, OpenAI APIs, vector databases, and graph databases.
• Ability to work with technical specifications, architecture patterns, and engineering standards.
• Strong problem-solving skills and ability to work in a fast-moving, delivery-focused environment.
• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field preferred.

Nice To Haves

• Experience contributing to production-grade systems is preferred.
• Experience working in specification-first, contract-driven, or Spec-Driven Development environments is considered an asset.
• Master’s degree is considered an asset.

Responsibilities

• Support GenAI initiatives from problem framing through production deployment and continuous improvement.
• Design, develop, and deploy single-agent and multi-agent systems.
• Build production-grade RAG and Graph RAG architectures.
• Develop enterprise-grade AI assistants, copilots, and workflow agents.
• Implement orchestration and handoff patterns across agentic workflows.
• Implement hallucination mitigation and response validation strategies.
• Build and maintain evaluation frameworks, guardrails, tracing, and production monitoring.
• Collaborate with data scientists, AI engineers, platform teams, and business stakeholders to deliver scalable AI solutions.
• Contribute to reusable components, engineering patterns, and technical standards for the AI Hub.
• Other duties as assigned.

Benefits

• Bonus at target

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level