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Postuler

Publié il y a 12 jours

Applied AI Engineer - Canada

@ Saransh Inc

Toutes ses offres

Montréal, Québec

Contrat3+ ans d’expérience
Postuler
SIGNAUX

Résumé des exigences :

  • Success in this role requires solid software engineering fundamentals, practical experience with AI application development, strong problem-solving skills, and the ability to communicate…
  • 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…

Outils et compétences

PythonLangChainCommunication skillsTest automationData protectionGitHubCI/CDCollaborationProblem solvingMicrosoft AzureAWSServiceNowJiraAtlassian Confluence
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-10-29
Première détection par notre source
2026-11-10
Mise à jour du dossier source
2026-11-10

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Postuler

Saransh Inc

Toutes ses offres
Description
Applied AI-Engineer Montreal (Canada)

Role Overview And Expectations

Applied AI engineers are hands-on developers who work collaboratively with business and technology teams to accelerate the implementation of Generative AI use cases across Morgan Stanley. Team members participate in discovery discussions, build and test prototypes, integrate AI capabilities with existing applications, and provide practical implementation support to sponsoring application development teams. Success in this role requires solid software engineering fundamentals, practical experience with AI application development, strong problem-solving skills, and the ability to communicate clearly and work effectively across teams.

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 modern 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.

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