Applied AI Engineer
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Montreal, QC, Canada (100% onsite, no remote or hybrid)
Interview:
May require an in-person interview
About the Role We’re looking for a hands-on Applied AI Engineer to help business and technology teams move Generative AI use cases from idea to working software at a major financial institution. You’ll join discovery discussions, build and test prototypes, integrate AI capabilities into existing applications, and support the application teams that sponsor them.
What You’ll Do
Take part in discovery with business and technology teams to shape Generative AI use cases
Build and test prototypes, proofs of concept, and reference implementations
Integrate AI capabilities with existing enterprise applications, data platforms, and APIs
Build AI agents, orchestration workflows, and tool integrations
Support sponsoring development teams with practical implementation help
Test and evaluate AI solutions for quality, safety, reliability, and performance
Required Qualifications
3 to 5 years of software engineering experience with hands-on application development
1 to 3 years building Generative AI applications, assistants, agents, copilots, or intelligent automation
Proficiency in Python, with experience building APIs, integrations, and enterprise applications
Working knowledge of LLMs, prompt engineering, embeddings, vector databases, semantic search, and RAG
Hands-on experience with AI frameworks such as LangGraph, LangChain, Claude Code SDK, or OpenAI SDK
Familiarity with Model Context Protocol (MCP), AI gateways, agent-to-agent communication, or tool-calling frameworks
Experience with GitHub, CI/CD pipelines, containers, and modern engineering practices
Familiarity with Azure or AWS services for hosting applications and AI workloads
Awareness of Responsible AI, AI governance, security controls, and enterprise data protection
Strong communication, collaboration, and problem-solving skills, with the ability to turn business requirements into working software
Preferred Qualifications
Experience with Azure AI Foundry, AWS Bedrock, Anthropic Claude, OpenAI GPT, Gemini, Grok, or similar platforms
Experience building RAG solutions, knowledge assistants, or AI-powered search
Exposure to multi-agent systems and orchestration workflows
Integration experience with ServiceNow, Jira, Confluence, SharePoint, Microsoft Graph, Databricks, or Snowflake
Familiarity with Kubernetes and cloud-native architectures
Experience in financial services or another regulated industry
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