Principal AI Engineer

RBC; Calgary; On-site; CAD 180,000 - 210,000; Full time

Benefits offered by this job

Total rewards program

Bonuses and flexible benefits

Stock options where applicable

Job summary

RBC Borealis, Calgary, seeks a Principal AI Engineer to lead data engineering on enterprise data and AI hybrid multi-cloud platforms. You will drive design, development, and deployment of data solutions and mentor a growing team of data engineers in a fast-paced environment.

You’ll collaborate with researchers, build agentic systems, and deliver robust AI workflows with strong governance, security, and observability.

Qualifications

• Bachelor’s degree in computer science or related technical field involving coding, or equivalent technical experience.
• 10+ years of professional software engineering experience with strong Python and SQL; Spark and Databricks SQL are a plus.
• Experience designing and operating scalable data architectures, including schema design and data lifecycle management.
• Knowledge of algorithms, data structures, systems engineering fundamentals, reliability, performance, and debugging.
• Hands-on experience with data engineering platforms and tools (Python, PySpark, Databricks, Airflow, Kafka, Snowflake).
• Experience building production services and APIs with authentication/authorization and integration patterns (Node.js, Apigee).
• Experience delivering AI-powered systems including RAG, vector search, LLM applications, prompts/orchestration, evaluation and lifecycle management.

Responsibilities

• Oversee end-to-end data integration, including sourcing, lineage, transformation, and storage for AI and analytics.
• Collaborate with Architecture, Business SME and Data Stewards.
• Architect and implement agentic systems with tools, workflow orchestration, and multi-step reasoning pipelines.
• Design and deliver Retrieval Augmented Generation solutions with document ingestion, indexing, and grounding strategies.
• Build evaluation harnesses, golden datasets, regression suites, and metrics for performance and cost.
• Implement observability: tracing, telemetry, drift detection, and runbooks for production ops.
• Lead batch and real-time data pipelines powering analytics and AI use cases.
• Design governed data products with contracts, lineage, and SLAs.
• Establish high-quality ingestion and transformation patterns using lakehouse/warehouse paradigms.
• Partner with data stewards to define data standards and metadata for trust.
• Build backend services and APIs exposing data products and AI workflows.
• Apply engineering practices: CI/CD, testing, performance, security by default.
• Develop scalable runtime patterns including caching, rate limiting, and idempotency.
• Contribute to reference architectures and reusable libraries.

Skills

Python

SQL

Spark

Databricks

Machine Learning

Education

Bachelor's degree in Computer Science or related field

Tools

Airflow

Kafka

Snowflake

Databricks

Node.js

Apigee

GitHub Actions

Job description

What's the opportunity?

We are looking for a Principle AI Engineer to drive the development of Data engineering solutions on RBC’s Enterprise Data and AI Hybrid Multi-cloud Platforms, that meet the strategic data objectives of the business. This is unique opportunity to be an impactful Data Engineering leader on a fast growing team.

Job Description

We are looking for a Principle AI Engineer to drive the development of Data engineering solutions on RBC’s Enterprise Data and AI Hybrid Multi-cloud Platforms, that meet the strategic data objectives of the business. This is unique opportunity to be an impactful Data Engineering leader on a fast growing team.

The successful candidate will be responsible for leading the design, development, and implementation of data solutions, as well as lead, mentor, and grow a team of talented data engineers. This role requires strong data engineering skills and leadership, effective written and verbal communication skills, a strong work ethic and a demonstrated capability to multi-task effectively as a member of a dynamic, fast paced team.

At RBC Borealis, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.

Your responsibilities include:

• Oversee end-to-end data integration, including sourcing, lineage, transformation, and storage to enable complex AI and advanced analytics, leveraging extensive technical expertise.
• Collaborate with Business architecture, System architecture, Business SME and Data Stewards.
• Architect and implement agentic systems, including tool using agents, workflow orchestrators, and multi step reasoning pipelines that reliably execute business tasks.
• Design and deliver Retrieval Augmented Generation solutions, including document ingestion, chunking, indexing, vector search, hybrid search, reranking, and grounding strategies over curated data products.
• Build evaluation harnesses and quality gates, including offline test sets, golden datasets, regression suites, and metrics for factuality, safety, latency, cost, and business outcomes.
• Implement observability for AI systems, including tracing across prompts and tool calls, telemetry, drift detection, and runbooks for production operations
• Lead the build of batch and real time data pipelines, including inbound, outbound, and event driven flows that power analytics and AI use cases.
• Design governed data products with clear contracts, documentation, lineage, and SLAs, enabling consistent consumption across domains.
• Establish high quality ingestion, transformation, and serving patterns using lakehouse and warehouse paradigms, plus streaming where appropriate.
• Partner with data stewards and domain teams to define data standards, quality controls, and metadata that ensure trust and reusability
• Design and build backend services and APIs that expose data products, agent capabilities, and AI workflows as reliable, secure services.
• Apply rigorous engineering practices, including code quality, automated testing, CI/CD, performance engineering, and secure by default design.
• Build scalable runtime patterns for AI systems, including caching, rate limiting, concurrency control, idempotency, and graceful degradation.
• Contribute to reference architectures, reusable libraries, and platform components that accelerate delivery across teams.

You're our ideal candidate if you have:

• Bachelor’s degree in computer science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience.
• 10+ years of professional software engineering experience with strong Python and SQL, Spark and Databricks SQL are a plus.
• Demonstrated experience designing and operating scalable data architectures, including schema design, dimensional modeling, and data lifecycle management.
• Strong knowledge of algorithms and data structures, plus systems engineering fundamentals, reliability, performance, and debugging.
• Hands on experience with data engineering platforms and tools, commonly including Python, PySpark, Databricks, Airflow, Kafka, Snowflake, and modern data integration patterns.
• Experience building production services and APIs, including service design, authentication and authorization, and integration patterns, Node.js and Apigee are a plus.
• Practical experience delivering AI powered systems, including one or more of:
• RAG systems and vector search, embeddings, reranking, and grounding strategies
• LLM application development, structured outputs, prompt and tool calling, orchestration patterns
• AI evaluation, test harnesses, regression testing, and lifecycle management for prompts and models
• Observability for AI systems, tracing, monitoring, alerting, and cost controls
• Working knowledge of security and identity frameworks such as OAuth 2.0, LDAP, Kerberos, and Vault integration, with experience operating in regulated environments.

Nice to have:

• Master’s degree in computer science or equivalent experience.
• Experience with agent frameworks and workflow patterns, such as graph based orchestration, tool routing, plan and execute loops, and human in the loop designs.
• MLOps and LLMOps experience, including CI/CD for ML and LLM applications, model registries, feature stores, experiment tracking, and safe rollout patterns
• Automation and DevOps experience, such as GitHub Actions, infrastructure as code, and automated QA.
• Experience working in Agile or SAFe environments.
• Experience with frontend or portal integration for AI experiences, for example Angular based portals, analytics integration, or enterprise enablement tooling.

What’s in it for you?

• Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
• Leaders who support your development through coaching and managing opportunities;
• Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

Job Skills

Big Data Analytics, Client Counseling, Coaching Others, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Results-Oriented, Software Engineering, Software Product Design

Additional Job Details

• Address: 407 8 AVE SW:CALGARY
• City: Calgary
• Country: Canada
• Work hours/week: 37.5
• Employment Type: Full time
• Platform: TECHNOLOGY AND OPERATIONS
• Job Type: Regular
• Pay Type: Salaried
• Posted Date: 2026-04-22
• Application Deadline: 2026-08-28
• Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

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