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Added 2 months ago
R
DataOps Engineer
RPIA
Toronto, ON
- Full-time
Strong SQL and database performance tuning experience.
Added 2 months ago
TR
AI Engineer, Product Analytics
Thomson Reuters
Toronto, ON · Canada, Toronto, Ontario
- Full-time
Proficiency in Python and strong SQL, with a solid grounding in programming concepts, design patterns, SDLC principles, and unit testing.
Added 2 months ago
A(
Machine Learning Resident - Client: Fillip Fleet
Amii (Alberta Machine Intelligence Institute)
Edmonton, AB
- Full-time
Proficiency in Python and modern AI frameworks such as Py
Added 2 months ago
BP
Full-Stack Engineer
Brightpathdigital Pro
Remote, Canada
- $30,000 to $40,000 USD / year
- Contract
- Remote
Design and build scalable backend services using Python and Node.js, with a strong focus on data integrity and reliability.
Added 2 months ago
Senior Manager, Supply Chain Analytics & Data Intelligence
Celestica International LP
Toronto, ON
We are seeking an experienced and strategic Senior Manager of Supply Chain Analytics & Data Intelligence to lead our supply chain data transformation. In this role, you will bridge the gap…
Added 2 months ago
Senior Consultant - Credit Risk Modelling - Montreal
EY
Montreal, QC
Significant experience and proven ability to program in pertinent languages, such as Excel, SAS, SQL, R, and Python.
Added 2 months ago
LT
Software Engineer
Larus Technologies
Ottawa, ON
- Full-time
5+ years of direct experience in design, development, deployment, and verification of software, with at least 2 years in Java and 2 years in python;
Added 2 months ago
Wayside Software Developer
Alstom
Saint-Bruno, QC
We are seeking a passionate Wayside Software Developer ready to shape modern rail solutions and enhance the safety and performance of mobility systems. You'll work alongside people who show…
Added 2 months ago
Full-Stack AI Engineer
Appnovation Technologies
Toronto, ON
Work with databases (SQL and NoSQL) to manage application data efficiently.
Added 2 months ago
GT
Python Developer
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- Contract
Modernize data engineering: Build and optimize data solutions using Python, PySpark, Azure Databricks, Delta Lake, ADLS, Azure Data Factory, Airflow, Azure SQL, Unity Catalog, and SQL.
Added 1 month ago
Staff Fullstack Automation & Integration Developer (Python)
AlayaCare
Montreal, QC
We are seeking a Staff Automation & Integration Developer and will be reporting to the Senior Director, Customer Engineering & Delivery. You will be working at the customer boundary to…
Added 2 months ago
GS
Consultant, Technical Solutions
Grantek Systems Integration
Burlington, ON
- Full-time
Perform scripting and development using Python and SQL, minimizing unnecessary customization
Added 2 months ago
H(
Sr. Manager, Performance Systems
HOOPP (Healthcare of Ontario Pension Plan)
Toronto, ON · CA ON Toronto
- Full-time
Build and maintain cross-functional reports and automation solutions using a range of reporting tools and technologies like Qlik, Python, Snowflake, Excel, Power BI, SAP Hana.
Added 2 months ago
MN
Solutions Architect
Modern Niagara
Hamilton, ON · Vaughan, ON
- Full-time
The Solution Architect leads the design, implementation, and continuous improvement of enterprise business systems that support Finance, Supply Chain, Operations, Manufacturing, and Project…
Added 2 months ago
C
Senior Data Platform Engineer
Clio
Toronto, ON
- Full-time
Programming proficiency in Python, Ruby, Go, or Scala for custom logging pipeline development and automation
Added 2 months ago
C
Senior Data Platform Engineer
Clio
Canada
- Full-time
Programming proficiency in Python, Ruby, Go, or Scala for custom logging pipeline development and automation
Added 2 months ago
C
Senior Data Platform Engineer
Clio
Calgary, AB
- Full-time
Programming proficiency in Python, Ruby, Go, or Scala for custom logging pipeline development and automation
Added 2 months ago
C
Senior Data Platform Engineer
Clio
Vancouver, BC
- Full-time
Programming proficiency in Python, Ruby, Go, or Scala for custom logging pipeline development and automation
Added 2 months ago
EA
AI Software Engineer
Eclipse Automation
Cambridge, ON
- Full-time
Build backend APIs, services, workers, and integration components using Python and one or more of .NET/C# or Node.js.
Added 2 months ago
A
BACKEND PYTHON DEVELOPER
Apexon
Toronto, ON
- Full-time
We are seeking a Senior Software Engineer to design and build highly scalable, secure, and high-performance solutions within our core banking platform. You will work in a cross-functional…
Added 2 months ago
AM
AI and Automation Software Engineer
Advanced Micro Devices, Inc
Vancouver, BC
- Full-time
Design, develop, test, and deploy automation solutions using Python and other relevant programming languages.
Added 2 months ago
M
Principal Software Engineer - Distributed Systems
Microsoft
Vancouver, BC
- Full-time
…integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure…
Added 2 months ago
GIS Developer
GeoLOGIC Systems Limited
Calgary, AB
We're growing and looking for a GIS Developer to join our team. In this role, you'll build and maintain the spatial data processes that sit at the heart of our organization, and help manage…
Added 2 months ago
Principal Data and Applied Scientist
SAP
Montreal, QC
Strong Python and SQL skills with production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Added 2 months ago
KS
Quality Assurance Automation Engineer
Kumaran Systems
Toronto, ON
- Full-time
Write and execute SQL queries to validate backend data integrity

SAP

Principal Data and Applied Scientist

Montreal, QC, H3B 0B3, Canada

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Job details

Experience: 8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.
Posting language: English
Posted: Aug 27, 2026

Original job description

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

Data and Applied Scientist

The context engine that makes AI enterprise ready.

Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As a Data and Applied Scientist at SAP, you'll build the context engine grounded in SAP’s Business ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.

Where you belong

You will be part of Data Labs within the CX Office of the CTO, a strategic organization embedded in SAP Customer Experience. We define the AI strategy and architecture vision for next-generation CX solutions and ensure seamless integration across the SAP ecosystem. Our team works collaboratively across SAP product units, engages deeply in technology strategy, and partners closely with customers and external communities. We strive to create meaningful impact through world-class architecture, innovation, and industry-driven expertise.

What you'll build

The semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. You'll build and scale the layer that makes that possible.

Design and maintain enterprise ontologies and semantic models that give AI agents accurate, grounded understanding of SAP and connected business landscapes harmonizing data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers into unified semantic layers.

Build AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production.

Develop AI capabilities including generative AI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets.

Leverage SAP's deep data and process context including SAP data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to ground AI solutions in real enterprise reality.

Work with cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP to support reliable, scalable AI workflows.

Partner across product, engineering, business, and customer-facing teams to translate ambiguous business challenges into concrete AI solutions from concept through deployment and continuous improvement.

Apply machine learning, deep learning, and statistical modeling to develop and evaluate AI solutions using real-world enterprise datasets.

What you'll bring

Required Qualifications

8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.

Master's or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field

Hands-on experience designing enterprise ontologies and semantic models; proficiency in at least one graph query language (SPARQL, Cypher, or GQL); understanding of trade-offs between RDF triple stores and property graph databases.

Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.

Strong Python and SQL skills with production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.

Proven track record deploying and operating AI/ML solutions in production including handoff, lifecycle support, and continuous improvement.

Experience with big data infrastructure and cloud environments Databricks or equivalent, plus at least one major cloud (AWS, Azure, or GCP).

Excellent communication and stakeholder management skills, with the ability to work cross-functionally in agile environments.

Preferred Qualifications

Deep working knowledge of SAP data models, metadata structures, and core business processes end-to-end. (SAP knowledge is a strong accelerator)

Hands-on experience with the SAP data and AI platform stack SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub.

Deep expertise across the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) and/or property graph query languages (Cypher, GQL).

Deep expertise in machine learning and deep learning, with experience developing, evaluating, and improving models on real-world datasets.

Experience with agentic AI, reasoning frameworks, planning, orchestration, tool use, or multi-agent architectures.

Experience contributing to reusable AI platforms, foundation model initiatives, or shared AI services adopted across multiple product areas.

Ability to design upper-level and mid-level ontologies aligned with industry standards and apply semantic interoperability frameworks across complex application landscapes.

Experience applying AI and semantic modeling to CX or Retail use cases such as personalization, pricing, product discovery, demand forecasting, or customer data unification across B2B and B2C contexts.

#dlhiring

Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.

For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP’s commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted combined range for this position is 144600-322500CAD. The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount, and any actual payout amount is dependent on company and personal performance. A summary of benefits and eligibility requirements can be found by clicking this link: www.SAPNorthAmericaBenefits.com.

Due to the nature of the role, which involves global interactions with SAP entities, as well as with employees and stakeholders in Canada, functional proficiency in English is required for positions based in the Quebec.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.

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More about this job

Responsibilities

You will design and maintain enterprise ontologies and semantic models to ground AI agents in real-world business context. Additionally, you will build and scale AI capabilities including RAG pipelines, embeddings, and knowledge graphs to ensure reliable performance in production.

Requirements

Candidates must have 8+ years of experience in knowledge engineering, semantic systems, or applied AI, along with a Master's or PhD in a quantitative field. Proficiency in Python, SQL, graph query languages, and modern GenAI frameworks is required.

Skills

Knowledge Engineering
Semantic Data Systems
Applied AI
Data Science
Python
SQL
PyTorch
TensorFlow
GenAI
RAG
Vector Databases
Knowledge Graphs
Machine Learning
Deep Learning
Cloud Computing
Ontology Design

Benefits

Health and well-being programs
Flexible working models
Continuous learning and skill growth
Professional development

Visa sponsorship

Not detected in the job text

Keywords

Knowledge Engineering
Semantic Modeling
GenAI
RAG
Vector Databases
Knowledge Graphs
Python
SQL
PyTorch
TensorFlow
Databricks
SAP HANA Cloud
Ontology
SPARQL
Cypher
GQL
Machine Learning
Deep Learning
Cloud Platforms
Enterprise Data
Business Ontology
Semantic Interoperability
Data Science
Artificial Intelligence
Software Development
Customer Experience
Metadata
Big Data
Agile
Stakeholder Management

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