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Lead Full Stack Engineer

Toronto, Ontario

Posted: 02/02/2026 Employment Type: Permanent Job Number: 8954

Job Description


Our client is seeking a high-caliber Lead Full Stack Engineer to join their organization. You will lead a high-performing agile team dedicated to designing, building, and maintaining scalable applications for global financial ecosystems. You will work across the entire stack—front-end, back-end, infrastructure, and data—to deliver secure, reliable, and innovative software solutions.

Key Responsibilities
  • Architectural Leadership: Lead the design of complex, distributed full-stack systems to improve reliability, security, and operational efficiency.
  • Technical Excellence: Set technical standards and best practices across multiple engineering teams.
  • Mentorship: Provide technical guidance and professional development.
  • Strategic Transformation: Drive platform modernization using new tools and technologies.
  • Cross-Functional Collaboration: Partner with technology and business leadership to deliver customer-focused results.

Required Qualifications
  • Experience: 8+ years of professional software engineering experience, with at least 3+ years in a leadership capacity over high-performance teams.
  • System Design: Proven track record of delivering and operating large-scale, enterprise-level production systems.
  • Backend Mastery: Proficiency in building Microservices and Spring Boot, with extensive experience in Java, SOAP, and JSON.
  • Infrastructure & DevOps: Deep experience with Cloud Foundry and Kubernetes.
  • SDLC & Tooling: Expertise in the full SDLC, version control, and CI/CD tools (Git, Bitbucket, Jenkins, Maven).
  • Data & Scripting: Proficiency in Unix tools, shell scripting (Bash, Python, Perl), and database management (SQL queries, PL/SQL, SQL Loader).

Nice to Have: AI & Data Engineering
  • Experience implementing AI/ML capabilities into production environments, including hands-on experience with AI APIs (OpenAI, Anthropic) and building LLM-powered features (chat, summarization, etc.).
  • Experience building data pipelines using Google Cloud Platform (GCP) services (DataProc, DBT, PubSub, Kafka, BigQuery, Cloud Spanner).
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