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Langgraph Jobs in Ontario (NOW HIRING)

Develop intelligent automation frameworks using LangChain and LangGraph to create context-aware agents that learn from incident patterns and continuously improve response strategies * Build ML ...

AI Engineer

Toronto, ON · On-site

CA$130K - CA$165K/yr

Evaluate AI frameworks and infrastructure (e.g., LangChain, LangGraph, AutoGen, LlamaIndex) and guide platform decisions Technical Execution * Diagnose and resolve complex AI system issues (retrieval ...

Evaluate Deep Agent, Claude Agent, OpenAI Agent, LangGraph, and other emerging agent orchestration patterns and frameworks for specific new use cases. * Build and maintain LLM evaluation systems ...

Proven experience with LangChain, LangGraph. Solid understanding of Retrieval-Augmented Generation (RAG), vector embeddings, semantic search. * APIs & Protocols: Strong experience with RESTful APIs ...

New

Experience with agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI) * Hands-on with AI observability tooling (LangSmith, LangFuse, Weights & Biases) * Familiarity with multi ...

Experience with LangChain, LangGraph, or similar LLM orchestration frameworks. Strong SQL skills and experience designing RESTful APIs. Experience with cloud-based LLM platforms (e.g., Azure OpenAI ...

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Langgraph information

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 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 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 popular job titles related to Langgraph jobs in Ontario?

For Langgraph jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in Ontario look for?

The top searched job categories for Langgraph jobs in Ontario are:

Infographic showing various Langgraph job openings in Ontario as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Staff AI Application Engineer

Royal Bank of Canada

Toronto, ON • On-site

Full-time

Posted 16 days ago


Job description

Job Description

What is the opportunity?

Join RBC as a hands-on technical lead building production-grade GenAI and Agentic AI applications for Cyber, Risk, Regulatory, Control & Security domains. This is an individual contributor role with no direct reports. You'll build the backend services that power autonomous and semi-autonomous AI agents, and work closely with AI Engineers to turn LangChain/LangGraph prototypes into production applications deployed on OpenShift through our CI/CD pipeline. If you want to write Python backend code, ship to production, and work at the intersection of software engineering and agentic AI in a regulated environment, this role is for you.

What will you do?

  • Build and deploy backend services for Agentic AI applications using Python Django (preferred) or FastAPI, with Celery for async task processing and long-running agent workflows.

  • Work with AI Engineers to productionize their agents and proof-of-concepts, turning LangChain/LangGraph prototypes into well-tested backend applications that run reliably in production.

  • Deploy and operate applications on OpenShift Container Platform (OCP) and Kubernetes, using the Helios CI/CD pipeline to ship frequently.

  • Build and maintain RESTful APIs that serve AI-powered applications, including authentication (OAuth2/JWT), rate limiting, input validation, and security controls appropriate for a regulated bank.

  • Integrate AI capabilities into backend services: RAG pipelines, MCP (Model Context Protocol), A2A (Agent-to-Agent Protocol), multi-agent systems, and LLM-powered workflows. Profile and optimize AI application performance, including LLM token cost management, caching strategies, latency reduction, efficient agent orchestration, and production observability using OpenTelemetry, Langfuse, or LangSmith.

  • Write unit and integration tests for backend services and agent workflows, and participate in code reviews to set the quality bar for the team.

  • Mentor other engineers on backend and productionization best practices, collaborate with product owners, data scientists, and business stakeholders, and contribute to secure coding and AI safety guardrails for a regulated financial services environment.

What do you need to succeed?

Must-Have:

  • 5+ years of software engineering experience with strong Python proficiency, including at least 2 years building backend services with Django, FastAPI, or a comparable framework.

  • Hands-on experience with Celery or similar async task processing for managing long-running or distributed workloads.

  • Strong understanding of API security, including authentication/authorization (OAuth2, JWT), rate limiting, input validation, and secure API design patterns.

  • Experience deploying and operating containerized applications on Kubernetes or OpenShift, and working with CI/CD pipelines (GitHub Actions, Jenkins, or equivalent).

  • Familiarity with GenAI application patterns such as RAG, Agents, Agent orchestration, MCP, A2A, and multi-agent systems. Some hands-on experience with LangChain, LangGraph, or similar frameworks is preferred.

  • Experience with AI observability and traceability tools (OpenTelemetry, Langfuse, or LangSmith), and proficiency with agentic coding tools (Claude Code, Cursor, Windsurf, Devin, or similar).


Nice to Have

  • Experience with PostgreSQL, Redis, or vector databases (pgvector, FAISS, Milvus).

  • Familiarity with Vue.js or React for occasional cross-stack work.

  • Exposure to LLM providers (OpenAI, Anthropic Claude, Cohere, Llama), prompt/context engineering, and LLM cost optimization techniques such as token tracking, prompt compression, caching, and model routing.

  • Familiarity with monitoring stacks (Grafana, Prometheus) and secure coding practices (SAST/DAST).

What's In For You?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.

  • Leaders who support your development through coaching and managing opportunities

  • Ability to make a difference and lasting impact

  • Work in a dynamic, collaborative, progressive, and high-performing team

  • Opportunities to take on progressively greater accountabilities.

  • Access to a variety of job opportunities across business and geographies.

#LI-POST
#TECHPJ

Job Skills

Back-End Development, Django Web Framework, Docker (Software), Generative AI, Integration Testing, Kubernetes, OAuth, Prometheus (Software), Python (Programming Language), Red Hat OpenShift, RESTful APIs

Additional Job Details

Address:

16 YORK ST:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-08-06

Application Deadline:

2026-08-31

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME