1

Langgraph Jobs in Quebec (NOW HIRING)

LangGraph * Vector Databases * RAG Architecture * Prompt Engineering * AI Governance Preferred Skills * Energy Operations Knowledge Management * Field Service Copilots * Asset Maintenance AI ...

Hands-on experience with tools such as LangChain, LangGraph, CrewAI, OpenAI APIs, vector databases, and graph databases. * Ability to work with technical specifications, architecture patterns, and ...

Leverage LangChain and LangGraph frameworks to read code, understand chain and graph construction, identify failure points, and write test harnesses. Validate integration points using MCPs, testing ...

next page

Showing results 1-20

Langgraph information

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.
What are popular job titles related to Langgraph jobs in Quebec? For Langgraph jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Langgraph jobs in Quebec look for? The top searched job categories for Langgraph jobs in Quebec are:
Infographic showing various Langgraph job openings in Quebec as of May 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 76% Physical, 5% Hybrid, and 19% Remote job distribution.

GenAI / LLM Architect (Energy) - GLAAS

NavitasPartners

Quebec, QC โ€ข On-site

Full-time

Posted 4 days ago


Job description

Job Title : GenAI / LLM Architect (Energy)Industry

Energy & Utilities

Position Overview

The GenAI Architect will lead the design and implementation of Generative AI solutions that improve operational efficiency, knowledge management, field service operations, asset maintenance, customer support, and energy market intelligence.

Responsibilities
  • Design enterprise GenAI architecture.
  • Build RAG-based AI solutions.
  • Develop domain-specific AI assistants.
  • Integrate LLMs with enterprise systems.
  • Establish AI governance and security controls.
  • Lead AI innovation initiatives across the organization.
Required Skills
  • Generative AI
  • Large Language Models (LLMs)
  • OpenAI APIs
  • Azure OpenAI
  • LangChain
  • LangGraph
  • Vector Databases
  • RAG Architecture
  • Prompt Engineering
  • AI Governance
Preferred Skills
  • Energy Operations Knowledge Management
  • Field Service Copilots
  • Asset Maintenance AI Assistants
  • Energy Market Intelligence Solutions
Mandatory Experience
  • 8+ years in Data & AI roles.
  • 3+ years in GenAI/LLM solutions.
  • Must have prior experience in the Energy, Utilities, Oil & Gas, Renewable Energy, or Energy Trading industry.


For more details reach at resumes@navitassols.com