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Graph Database Jobs in Ontario (NOW HIRING)

Expertise in teaching models to use external APIs, databases, and legacy tools effectively. You ... Experience with graph-based data structures is a plus. * Cloud Native Agent Infrastructure: Strong ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases. * DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps ...

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Showing results 1-20

Graph Database information

See Ontario salary details

$31K

$119.6K

$157.5K

How much do graph database jobs pay per year?

As of Jul 3, 2026, the average yearly pay for graph database in Ontario is $119,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,000.00 and $147,000.00 per year, depending on experience, location, and employer.

What is a Graph Database job?

A Graph Database job typically involves working with graph-based database technologies such as Neo4j, ArangoDB, or Amazon Neptune. Professionals in this role design, implement, and optimize graph database models to efficiently store and retrieve complex relationships between data points. Common responsibilities include data modeling, query optimization using graph query languages (e.g., Cypher, Gremlin), and integrating graph databases into larger data ecosystems. These roles are often found in industries like fraud detection, social networking, and recommendation systems, where understanding relationships between data is crucial.

What are the key skills and qualifications needed to thrive in the Graph Database position, and why are they important?

To thrive as a Graph Database Engineer, you need expertise in data modeling, query languages such as Cypher or Gremlin, and a solid understanding of graph theory and database architectures. Familiarity with graph database platforms like Neo4j, Amazon Neptune, or TigerGraph, as well as certifications in relevant technologies, are highly valued. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating with development and analytics teams. These competencies are vital for designing efficient graph data solutions, optimizing performance, and supporting business insights through connected data analysis.

What are some common challenges faced by professionals working with graph databases?

One common challenge when working with graph databases is efficiently modeling highly connected data structures to optimize for both query performance and scalability. Professionals must continuously evaluate indexing strategies and traversal queries to prevent bottlenecks as datasets grow. Another challenge is integrating graph databases with existing data pipelines or relational systems, which often requires specialized knowledge. However, these challenges offer opportunities to innovate and collaborate with cross-functional teams to deliver powerful solutions for complex data relationships.

What are popular job titles related to Graph Database jobs in Ontario? For Graph Database jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Graph Database jobs in Ontario look for? The top searched job categories for Graph Database jobs in Ontario are:
Infographic showing various Graph Database job openings in Ontario as of June 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 60% Physical, 4% Hybrid, and 36% Remote job distribution, with an average salary of $119,572 per year, or $57.5 per hour.
Senior AI Engineer

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago


Job description

Summary

What You'll Do
Orchestration Architecture: Define and drive the architecture for complex agentic flows, ensuring agents remain reliable, steerable, and seamlessly integrated into the Guidewire ecosystem.
Domain-Specific Reasoning: Work closely with subject matter experts to translate intricate insurance logic into agentic reasoning patterns (e.g., ReAct, Plan-and-Execute). You will ensure agents adhere to strict regulatory and business constraints.
Rapid Agent Prototyping: Design and oversee high-fidelity prototypes, exploring how agents can autonomously navigate insurance workflows to validate business relevance.
Agentic Reliability & Evals: Set the standard for evaluating non-deterministic agentic behavior. You will build rigorous frameworks to test for tool-calling accuracy, reasoning consistency, and safety guardrails to ensure production-readiness.
Agentic Observability & Tracing: Implement comprehensive monitoring and tracing for agentic decision-making processes. You will ensure full visibility into multi-step reasoning chains, state transitions, and tool-usage to facilitate debugging, auditability, and performance tuning in complex, asynchronous environments.
Engineering Collaboration: Partner with core engineering to build the specialized infrastructure required for long-running agentic tasks.
Applied Agentic Research: Act as SME on agentic AI, conducting deep research into emerging patterns like multi-agent collaboration, autonomous self-correction, and small language model (SLM) optimization for specific agentic tasks.
Mentorship & Excellence: Elevate the organization by mentoring engineers on agentic design patterns, fostering a culture of technical curiosity.
At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI-empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes.

Job Description

Requirements
  • Experience: 8+ years implementing ML/AI technologies, with at least 2 years focused on building and scaling LLM-driven applications.

  • Agentic Mastery: Proven track record of building and deploying agentic workflows. Deep expertise in orchestration frameworks (e.g., LangGraph).

  • Advanced Prompt Engineering & Tool-Use: Expertise in teaching models to use external APIs, databases, and legacy tools effectively. You should have a deep understanding of tool-calling, structured output generation, and context window management.

  • Domain Expertise: Demonstrated experience taking AI models from notebooks to high-availability environments within highly regulated industries (e.g., P&C Insurance, Banking, or Healthcare).

  • Technical Proficiency: Advanced Python skills; deep familiarity with state-of-the-art LLMs (OpenAI, Anthropic). Experience with graph-based data structures is a plus.

  • Cloud Native Agent Infrastructure: Strong experience with AWS or similar cloud providers, with a focus on building scalable, event-driven architectures that support asynchronous agent tasks.

  • Problem Solving: A creative builder mindset capable of architecting solutions in the face of the ambiguity inherent in greenfield agentic projects.

  • Communication: Exceptional ability to explain how and why an agent made a specific decision to executive stakeholders, maintaining transparency in autonomous systems.

  • Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement.

The Canadian CAD base salary range for this full-time position is - . Your base pay will depend on your experience, skills, education, training, and location among other factors. All full-time positions or part-time roles working 30 hours or more a week at Guidewire are eligible for benefits that support their health and well-being including health, dental, and vision insurance, paid time off, and a company sponsored retirement plan. In addition, some roles may be eligible for the annual company bonus plan, commissions, and/or long term incentive awards which are contingent on a variety of factors including, but not limited to, company and employee performance.

About Guidewire

Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service. More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire.

As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation.

For more information, please visit www.guidewire.com and follow us on Twitter: @Guidewire_PandC.

Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success. Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.