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Publié il y a 8 jours

Applied AI Engineer (Generative AI & Agentic Apps) - Onsite Only

@ Vivid Soft Global

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Montréal, Québec

Contrat
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SIGNAUX

Responsabilités :

  • 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

Résumé des exigences :

  • Required Qualifications
  • 3 to 5 years of software engineering experience with hands-on application development
  • 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
  • Experience with GitHub, CI/CD pipelines, containers, and modern engineering practices
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-11-02
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

Vivid Soft Global

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ChampValeur
Offres sur Jobsy1
Description

Applied AI Engineer (Generative AI & Agentic Apps) | Montreal, QC (100% Onsite)

Location: 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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