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Langgraph Jobs in Quebec (NOW HIRING)

Strong proficiency in Python and experience with AI/ML frameworks (e.g., LangChain, LangGraph, FastAPI). * Solid experience with AWS services relevant to AI/ML workloads (e.g., Bedrock, AgentCore ...

Familiarity with AI agent frameworks and orchestration tools (LangGraph, LangChain, CrewAI, or similar) and agent harness * Experience with model explainability techniques (SHAP, LIME) and bias ...

New

Experience designing and deploying production AI systems (e.g., APIs, microservices, or agent-based systems) Familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph) and vector ...

Familiarity with AI agent frameworks and orchestration tools (LangGraph, LangChain, CrewAI, or similar) and agent harness * Experience with model explainability techniques (SHAP, LIME) and bias ...

New

... LangGraph) et les bases de donnees vectorielles Experience des pratiques MLOps, notamment la gestion des modeles et des versions, les pipelines d'evaluation et la surveillance Solide comprehension ...

... LangGraph, LangChain, CrewAI, or similar) and agent harness Experience with model explainability techniques (SHAP, LIME) and bias/fairness assessment in production contexts Knowledge of the full ...

New

Familiarité avec les agents IA et les outils d'orchestration (LangGraph, LangChain, CrewAI ou similaires) et les environnements de test d'agents * Expérience des techniques d'explicabilité des ...

New

... LangGraph, LangChain, CrewAI ou similaires) et les environnements de test d'agents Expérience des techniques d'explicabilité des modèles (SHAP, LIME) et de l'évaluation des biais et de l'équité ...

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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 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 July 2026, with employment types broken down into 11% Internship, 78% Full Time, and 11% Contract. Highlights an 78% In-person, and 22% Hybrid job distribution.
Technical Lead, Cybersecurity Engineering - Agentic AI (Hybrid)

Technical Lead, Cybersecurity Engineering - Agentic AI (Hybrid)

Morgan Stanley

Montreal, QC • Hybrid

Full-time

Posted 22 hours ago


Morgan Stanley rating

8.3

Company rating: 8.3 out of 10

Based on 154 frontline employees who took The Breakroom Quiz

40th of 148 rated financial services


Job description

We're seeking someone to join our team as a Technical Lead, Cybersecurity Engineering to help drive the development of security controls that ensure the firm's Agentic AI information assets comply with internal and external regulations.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Cyber Security Engineering position at Vice President level, which is part of the job family responsible for providing specialist cyber expertise and creating solutions that protect the organization's systems and networks against actual and potential security threats and vulnerabilities.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on...

What you'll do in the role:

  • Develop and execute the cybersecurity engineering strategy in line with organizational goals.

  • Oversee the implementation of security programs and initiatives across the organization.

  • Drive the adoption of AI security best practices and ensure team compliance with security policies.

  • Collaborate with technology and business leaders to ensure a cohesive and enterprisewide security posture.

  • Communicate regularly with product leads across the technology organization to identify opportunities to improve existing and future technology solutions.

  • Ensure the effective management of security incidents and lead postincident review processes.

  • Report on security metrics and performance to senior management and key stakeholders.

What you'll bring to the role:

  • Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent practical experience.

  • At least 5 years of experience in security control and enterprise software development

  • AT least 5 years of programming experience with Python

  • At least 2 years of hands-on experience with LLM and Agentic AI

  • Hands on experience with AI framework/SDK, LangGraph, Google ADK, CrewAI will be a plus

  • Hands on experience with RDBMS or NoSQL database (Snowflake, PostgreSQL) will be a plus

  • Experience with Red teaming, incident management will be a plus

  • Indepth knowledge of Agentic AI, security frameworks, risk management, and incident response.

  • Excellent communication and interpersonal skills, with the ability to influence and engage effectively with senior stakeholders.

At Morgan Stanley Montreal, we support the Firm's global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, cloud engineering, infrastructure, cybersecurity and AI/ML. Morgan Stanley has been rooted in the Montreal community since 2008 and is considered a leading employer among the area's highly skilled technology talent. There's ample opportunity to move across the businesses for those who show passion and grit in their work.

All our positions are located in Montreal, Quebec. We offer a hybrid work environment, combining remote work and attendance in the office.

Knowledge of French and English is required.

Build a career with impact. Visit morganstanley.com for more information.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.


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