Data/AI Engineering Team Lead

RBC•Toronto, ON

1d•Onsite

About The Position

We are seeking a Data/AI Engineering Team Lead to deliver data-driven and AI-powered business solutions within Personal and Commercial Banking. You will work closely with business stakeholders, product teams, architects, and technology partners to solve complex business challenges through innovative use of data, software, automation, and AI. This role combines people leadership, solution delivery, and technical oversight across the full solution lifecycle from concept through production. You will help accelerate enterprise adoption of AI capabilities that improve client experiences, increase operational efficiency, and drive business growth. This is an opportunity to lead high-impact initiatives while developing and mentoring a team of talented engineers.

Requirements

Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, or a related field.
7+ years of experience delivering enterprise software, data, integration, or AI solutions, including 2+ years leading engineering teams.
Strong software engineering expertise with hands-on experience in Python and at least one of Java or Scala for building production-grade applications and services.
Experience designing and implementing data pipelines, APIs, event-driven architectures, workflow orchestration, and distributed systems using technologies such as Snowflake, Spark, Airflow, Kafka, OpenShift, and AWS.
Proven experience implementing DataOps, AIOps, and DevOps practices, including CI/CD, infrastructure automation, observability, data quality controls, monitoring, and governance.
Strong communication and stakeholder management skills, with the ability to translate business requirements into scalable, secure, and reliable technology solutions.

Responsibilities

Lead the technical design and delivery of data and AI solutions while providing day-to-day guidance and mentorship to a team of engineers.
Collaborate with business stakeholders, product teams, and architects to translate business requirements into scalable, secure, and production-ready solutions.
Design and develop data pipelines, APIs, integrations, AI-powered applications, and workflow automation capabilities that deliver measurable business value.
Champion engineering best practices across software development, DataOps, AIOps, CI/CD, testing, observability, and Site Reliability Engineering (SRE) to improve solution quality and reliability.
Contribute hands-on to solution development, code reviews, troubleshooting, production support, and technical decision-making while helping grow the technical capabilities of the team.