Senior Applied AI Engineer

Location: Montreal

Compensation: $, - , plus up to $20, bonus, capped at %

Job Summary

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

Primary Responsibilities

Own GenAI initiatives end-to-end from problem framing through production deployment and continuous monitoring

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

Design orchestration and handoff patterns across multi-agent workflows

Implement hallucination mitigation and response validation strategies

Build evaluation frameworks, guardrails, tracing, and production monitoring

Other duties as assigned

Qualifications, Experience and Educational Requirements

Work Experience:

Three + years of hands-on experience in Generative AI engineering, LLM systems, or Applied AI since onward, with proven experience delivering production-grade GenAI solutions

Five + years of prior experience in Python software engineering, backend engineering, platform engineering, or related software development roles

Proven track record of building and deploying production systems, APIs, workflow orchestration services, or distributed applications prior to working in GenAI

Skills and

Competencies:

Strong expertise in LLM systems engineering, prompt engineering, RAG, Graph RAG, agent orchestration, multi-agent systems, 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 Lang Chain, Lang Graph, CrewAI, OpenAI APIs, vector and graph databases

Experience working in specification-first, contract-driven, or Spec-Driven Development (SDD) environments is considered a strong asset

Education:

Master’s degree or Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field preferred