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AI-Augmented Full-Stack Engineer - Vice President

Job in Mississauga, Ontario, Canada
Listing for: Citigroup Inc.
Full Time position
Listed on 2026-09-01
Job specializations:
  • Software Development
    Full Stack Developer, Software Architect, Backend Developer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 168000 - 237000 CAD Yearly CAD 168000.00 237000.00 YEAR
Job Description & How to Apply Below

About the Role:

Where Your Engineering Actually Ships

The AI-Augmented Full-Stack Engineer is a senior individual contributor position within Citi's Banking Technology organization. This team
builds and maintains the applications and platforms that put real capital to work for clients across one of the world's largest financial institutions.

This is a hands‑on engineering role. You will design, develop, and ship full-stack solutions while helping shape how the team builds software - embedding AI into the engineering craft as a natural and practical part of daily work, not as an afterthought.

If you are a senior engineer who writes excellent code, thinks clearly about systems, and wants to work on problems that matter - this role was written for you.

Key Responsibilities
  • Full-Stack Design and Delivery: Design, develop, and deliver full-stack applications using Java and Spring Boot on the backend and Angular on the frontend, with meaningful input into technical direction and architectural decisions.

  • AI-Augmented Engineering Practice: Embed AI development tools such as Devin, Git Hub Copilot, Claude, and Codex into your daily engineering workflow as the default way of working - and actively drive that same adoption across the team. Establish shared standards for prompt engineering, code review, and quality guardrails so that AI-augmented development becomes the team's natural practice, not the exception.

  • Technical Leadership and Engineering Excellence: Set the technical bar for the team through thoughtful code reviews, clear architectural guidance, and hands‑on problem solving. Mentor mid-level engineers not through instruction alone, but by demonstrating what excellent engineering looks like in practice every day.

  • Data Management and Architecture: Apply sound data design principles across both relational and No

    SQL databases - Oracle and MongoDB - with a focus on data integrity, schema design, and query performance. Champion data standards that keep systems maintainable and trustworthy at scale.

  • Cloud‑Native Engineering Mindset: Bring a strong conceptual understanding of modern cloud-native principles - infrastructure as code, containerization with Docker and Open Shift, Kubernetes‑based orchestration, and engineering practices that optimize for delivery throughput and system stability. You do not need to own the pipes, but you need to think about them.

  • Engineering Judgement and Accountability: Make decisions with the full picture in mind - technical quality, business impact, security, and regulatory context. Bring the kind of professional judgement that earns trust with stakeholders and keeps the team building with confidence.

What You Bring

Experience and Qualifications

  • 6+ of software engineering experience, with meaningful time in a senior, lead, or principal capacity on complex, enterprise‑grade systems

  • Experience delivering software in a financial service, fintech, or similarly regulated, high-complexity environment

  • Proven ability to provide technical leadership and mentor engineers in a senior individual contributor capacity

  • Strong communication skills, with the ability to articulate technical concepts clearly to engineering and business audiences alike

  • Bachelor's degree in computer science, Engineering, or equivalent experience

Technical Skills

  • Backend: Strong working knowledge of Java and the Spring Framework ecosystem

  • Frontend: Hands‑on experience with Angular. Familiarity with React or other modern frameworks is a plus

  • Databases: Working knowledge of both relational and No

    SQL databases, including Oracle and MongoDB

  • AI Fluency: Practical, daily use of AI coding tools with a solid conceptual understanding of how they work - including prompt engineering, context window management, retrieval‑augmented generation (RAG), tokenization, and grounding techniques. You know enough about what is happening under the hood to use these tools with intention, not just habit

  • Cloud Awareness: Familiarity with cloud-native concepts - containerization, infrastructure as code, CI/CD practices, and delivery metrics such as DORA. Comfortable reasoning about system design in a cloud-native context

Preferred
  • Experience with Angular…

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