Required Qualifications

- 3 to 5 years of software engineering experience with hands-on application development responsibilities.
- 1 to 3 years of practical experience developing Generative AI applications, AI assistants, AI agents, copilots, or intelligent automation solutions.
- Proficiency in Python and experience building APIs, integrations, and enterprise applications.
- Working knowledge of Large Language Models (LLMs), prompt engineering, embeddings, vector databases, semantic search, Retrieval-Augmented Generation (RAG), and common AI application patterns.
- Hands-on experience with one or more AI development frameworks, such as LangGraph, LangChain, Claude Code SDK, OpenAI SDK, or similar technologies.
- Familiarity with Model Context Protocol (MCP), AI gateways, agent-to-agent communication, or tool-calling frameworks.
- Experience implementing AI agents, orchestration workflows, tool integrations, or agentic applications.
- Experience building proofs of concept, prototypes, or reference implementations.
- Experience integrating applications with enterprise systems, data platforms, and APIs.
- Familiarity with automated testing and evaluation approaches for AI solution quality, safety, reliability, and performance.
- Awareness of Responsible AI principles,



AI governance, security controls, and enterprise data protection requirements.
- Experience with GitHub, CI/CD pipelines, containers, and contemporary software engineering practices.
- Familiarity with Azure or AWS services used to host and operate applications and AI workloads.
- Ability to work with business stakeholders and application development teams to translate requirements into working software.
- Strong communication, collaboration, and problem-solving skills.

Preferred Qualifications

- Experience with Azure AI Foundry, AWS Bedrock, Anthropic Claude, OpenAI GPT models, SpaceX Grok Models, Gemini, or similar enterprise AI platforms.
- Experience building RAG solutions, knowledge assistants, or AI-powered search capabilities.
- Exposure to multi-agent systems and agent orchestration workflows.
- Experience integrating applications with ServiceNow, Jira, Confluence, SharePoint, Microsoft Graph, Databricks, Snowflake, or similar enterprise platforms.
- Familiarity with Kubernetes, containerized application deployment, and cloud-native architectures.
- Experience working in financial services or another regulated industry.

📌 Applied AI Engineer (Montreal)
🏢 Astek
📍 Montreal