Director, AI Engineering & Full-Stack Development

Royal Bank of Canada•Jersey City, NJ

23h•Onsite

About The Position

As Director of AI Engineering & Full-Stack Development in RBC Capital Markets, you will lead a team of AI engineers and architects responsible for designing, evaluating, and deploying ethical, compliant, and operationally transformative AI solutions. This role combines strategic technology leadership with hands-on oversight of cutting-edge AI and full-stack development initiatives. You will analyze and recommend AI technology stacks, cultivate strategic vendor and technology partnerships, and drive the architectural vision that enables Capital Markets digital innovation while maintaining the highest standards of governance and responsibility. This leadership role centers on building and scaling an AI engineering capability that transforms operations across RBC Capital Markets. You will oversee the evaluation and adoption of emerging AI technologies, guide your team through complex technical decisions, and ensure all solutions align with RBC's ethical AI principles, regulatory requirements, and risk management frameworks. You will serve as a strategic bridge between business stakeholders, engineering teams, and executive leadership, translating business imperatives into robust technical strategies and fostering a culture of innovation, accountability, and continuous learning.

Requirements

Minimum 10+ years of full-stack development and 5+ years of AI/ML engineering experience, with at least 3 years in a leadership or senior technical role.
Deep expertise in modern AI technologies, including generative AI, LLMs, machine learning frameworks, and related platforms.
Advanced proficiency in at least one primary programming language (.NET Framework, Python, or equivalent) and demonstrated breadth across multiple platforms.
Strong experience with API integration, microservices architecture, and cloud-native development.
Experience with MCP (Model Context Protocol) servers and emerging AI infrastructure standards.
Hands-on understanding of the full development lifecycle, including design patterns, testing frameworks, deployment pipelines, and DevOps practices.
Demonstrated experience evaluating, selecting, and implementing technology stacks and vendor solutions.
Proven track record of leading engineering teams, mentoring talent, and building high-performance cultures.
Excellent communication skills, verbal, written, and presentation, with the ability to translate complex technical concepts for diverse audiences.
Strong understanding of ethical AI principles, responsible AI governance, compliance frameworks, and risk mitigation strategies.
Ability to think strategically about technology investment and business value while maintaining hands-on technical judgment.
Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, or equivalent professional experience.
Exceptional relationship management skills and ability to build trust across the enterprise with stakeholders, partners, and teams.

Nice To Haves

Experience in capital markets, financial services, or regulated industries.
Knowledge of technology landscape, architecture standards, or enterprise governance frameworks.
Familiarity with AI safety, model governance, or responsible AI frameworks
Background in process automation, workflow optimization, or business architecture.
Exposure to Agile/Scrum methodologies and experience scaling development practices across teams.

Responsibilities

Lead and mentor an engineering team through design, development, and deployment of enterprise AI solutions.
Evaluate and recommend AI technology stacks, architectures, and vendor partnerships aligned with business needs and organizational standards.
Promote ethical AI governance frameworks, ensuring all solutions incorporate responsible AI principles, bias detection, and compliance mechanisms.
Partner with business leaders to identify high-impact automation and AI opportunities and quantify their operational and financial benefits.
Drive architecture reviews, technical governance, and quality standards across all AI initiatives.
Build and maintain strategic relationships with AI technology vendors, research institutions, and thought leaders.
Communicate AI strategy, roadmap, and technical insights to executive stakeholders and engineering teams.
Lead cross-functional workshops to define requirements, resolve technical challenges, and align expectations.
Foster a culture of continuous learning, innovation, and operational excellence within your team.
Ensure all solutions maintain compliance with regulatory requirements, data governance, and RBC risk management frameworks.