Principal AI Engineer, Agentic Models and Data Platforms
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Key skills for this role
About the Role
RBC is seeking a Principal AI Engineer to drive the development of scalable data pipelines and agentic AI systems on enterprise hybrid multi-cloud platforms. The role involves architecting RAG solutions, building evaluation harnesses, and leading data engineering teams.
Key Skills for This Role
Responsibilities
- Architect and implement agentic systems including tool using agents and multi step reasoning pipelines
- Design and deliver Retrieval Augmented Generation solutions
- Build evaluation harnesses and quality gates for AI systems
- Implement observability for AI systems including tracing and drift detection
- Lead the build of batch and real time data pipelines
- Design governed data products with clear contracts and SLAs
- Establish high quality ingestion, transformation, and serving patterns
- Design and build backend services and APIs for data and AI workflows
- Apply rigorous engineering practices including CI/CD and automated testing
- Build scalable runtime patterns for AI systems
Requirements
- Bachelor's degree in computer science or related technical field, or equivalent experience
- 10+ years of professional software engineering experience with strong Python and SQL
- Experience designing and operating scalable data architectures
- Hands on experience with data engineering platforms (Python, PySpark, Databricks, Airflow, Kafka, Snowflake)
- Experience building production services and APIs
- Practical experience delivering AI powered systems (RAG, LLM, AI evaluation, observability)
- Working knowledge of security frameworks (OAuth 2.0, LDAP, Kerberos, Vault)
Full Job Posting
Job Description
- Drive the development of scalable, high performance data pipelines within the Enterprise Data Platforms for enabling seamless access to and analysis of data across the organization.
- We are seeking a Data Engineering leader to drive the development of Data engineering solutions on RBC’s Enterprise Data and AI Hybrid Multi cloud Platforms.
What will you do?
- Architect and implement agentic systems, including tool using agents, workflow orchestrators, and multi step reasoning pipelines.
- Design and deliver Retrieval Augmented Generation solutions, including document ingestion, chunking, indexing, vector search, hybrid search, reranking, and grounding strategies.
- Build evaluation harnesses and quality gates, including offline test sets, golden datasets, regression suites, and metrics.
- Implement observability for AI systems, including tracing across prompts and tool calls, telemetry, drift detection.
- Lead the build of batch and real time data pipelines, including inbound, outbound, and event driven flows.
- Design governed data products with clear contracts, documentation, lineage, and SLAs.
- Establish high quality ingestion, transformation, and serving patterns using lakehouse and warehouse paradigms.
- Partner with data stewards and domain teams to define data standards, quality controls, and metadata.
- Design and build backend services and APIs that expose data products, agent capabilities, and AI workflows.
- Apply rigorous engineering practices, including code quality, automated testing, CI/CD, performance engineering.
- Build scalable runtime patterns for AI systems, including caching, rate limiting, concurrency control, idempotency.
- Contribute to reference architectures, reusable libraries, and platform components.
Must Have
- 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.
- Demonstrated experience designing and operating scalable data architectures.
- Strong knowledge of algorithms and data structures, plus systems engineering fundamentals.
- Hands on experience with data engineering platforms and tools, commonly including Python, PySpark, Databricks, Airflow, Kafka, Snowflake.
- Experience building production services and APIs, including service design, authentication and authorization.
- Practical experience delivering AI powered systems, including one or more of: RAG systems, LLM application development, AI evaluation, observability for AI systems.
- Working knowledge of security and identity frameworks such as OAuth 2.0, LDAP, Kerberos, and Vault integration.
Nice to have
- Master’s degree in computer science or equivalent experience.
- Experience with agent frameworks and workflow patterns.
- MLOps and LLMOps experience, including CI/CD for ML and LLM applications.
- Automation and DevOps experience, such as GitHub Actions, infrastructure as code.
- Experience working in Agile or SAFe environments.
- Experience with frontend or portal integration for AI experiences.
What’s in it for you?
- 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.
- A world class training program in financial services.
- Opportunities to do challenging work.
Additional Job Details
- Address: 335 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
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