Senior Software Engineer, Full-Stack Applications - Ratings Technology

Fitch Group • Toronto, ON

5d • CA$130,000 - CA$180,000 • Onsite

About The Position

Fitch Ratings is seeking a Senior Software Engineer to join its new AI Innovation teams in Toronto, focused on building AI-powered platforms and applications to transform financial analysis. This role involves leading the development of intelligent applications and full-stack platforms that integrate AI capabilities, aiming to change how Ratings analysts work and how Fitch delivers insights. The company is making a significant strategic investment in AI, with Toronto as its innovation center, building teams of full-stack and ML engineers. The Senior Software Engineer will own critical components of applications and infrastructure, drive technical decisions, architect scalable solutions, implement backend services, and create integrations for ML models. The role requires experienced full-stack engineers who understand AI's potential and can lead technical initiatives, architecting solutions that leverage generative AI, intelligent automation, and ML. This is a high-impact role for those energized by innovation and pushing technological boundaries, offering the chance to work alongside talented ML engineers, mentor others, and drive technical excellence.

Requirements

• Deep full-stack engineering expertise – 12+ years of hands-on experience building web applications, with expert-level proficiency in Java, Springboot, Python, REACT, and modern web technologies; proven track record of delivering complex, production-quality full-stack solutions at scale
• Polyglot programming mastery – Extensive professional experience with both Java and Python; ability to drive technical decisions across different technology stacks and architect solutions that span diverse codebases
• Strong architectural and design expertise – Proven experience designing maintainable, scalable systems; deep understanding of design patterns, RESTful APIs, microservices, distributed systems; ability to make and own architectural decisions that impact multiple teams
• Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience)
• Mastery of modern development practices – Expert knowledge of software development fundamentals including test-driven development, advanced Git workflows, sophisticated CI/CD pipelines, and driving code quality across teams
• Leadership and collaboration skills – Proven ability to lead cross-functional teams, mentor engineers, influence technical direction, communicate complex technical concepts to diverse audiences, and drive alignment across ML engineers, product, and stakeholders
• Strategic mindset with AI understanding – Solid understanding of how AI/ML and generative AI can transform workflows; experience evaluating emerging technologies; comfort with technical ambiguity; track record of driving adoption of AI-powered capabilities in production applications
• Advanced problem-solving and technical depth – Exceptional analytical skills, experience navigating complex technical challenges, ability to drive multiple strategic initiatives, and proven success tackling sophisticated problems at the intersection of full-stack engineering and AI

Nice To Haves

• Cloud-native architecture expertise – Deep hands-on experience with Docker, Kubernetes/EKS, AWS/Azure, microservices architecture, sophisticated CI/CD pipelines, and architecting cloud-native solutions at scale
• AI integration and production experience – Hands-on experience architecting and implementing AI/ML capabilities in production applications, working with LLM APIs, generative AI services, or building systems that leverage emerging AI technologies; proven track record making AI useful in production environments
• API architecture and system integration expertise – Expert experience designing scalable RESTful APIs, architecting complex integrations, designing asynchronous workflows, and creating robust interfaces between systems
• Advanced frontend architecture – Deep expertise with modern REACT patterns, complex state management, performance optimization, and architecting intuitive user experiences for sophisticated functionality
• Technical leadership in innovation environments – History of leading technical initiatives in fast-paced environments, driving architectural decisions for greenfield products, or owning technical direction in early-stage initiatives built from the ground up
• Mentorship and technical influence – Proven track record of mentoring engineers, driving technical growth across teams, leading code review culture, and establishing engineering best practices; recognized as a technical leader by peers
• Financial services or complex domain expertise – Deep understanding of analytical workflows, financial products, or complex business domains; experience translating business complexity into elegant technical solutions
• Technical thought leadership – Active participation in Toronto's tech community, speaking at meetups or conferences, contributing to open source, or recognized expertise in relevant technical domains
• Passion for engineering excellence and architecture – Drive high standards for architectural practices, clean code, comprehensive testing, and maintainable systems; recognized for technical craftsmanship and establishing quality standards
• Track record of technical evolution – Demonstrated history of driving technology adoption, leading architectural transformations, and expanding technical capabilities across teams and organizations.

Responsibilities

• Architect and lead full-stack applications – Design and drive implementation of scalable application features using Java/Springboot, Python, and REACT; own architectural decisions for user interfaces, backend services, APIs, and infrastructure; establish technical patterns that make AI capabilities accessible and maintainable
• Lead AI/ML integration architecture – Drive the technical approach for integrating generative AI, LLMs, and intelligent automation into full-stack applications; establish patterns for connecting ML models with user experiences; own technical decisions on how AI features are architected and implemented
• Champion engineering excellence – Establish and enforce engineering best practices, conduct code reviews, mentor engineers on code quality, drive CI/CD pipeline improvements, and lead technical discussions that balance innovation with reliability; own technical debt management and architectural improvements
• Drive technical decisions across teams – Lead collaboration with ML engineers, product managers, and business stakeholders; influence technical strategy; facilitate architectural discussions; and ensure alignment between AI innovation and application delivery through technical leadership
• Mentor and elevate team capabilities – Provide technical mentorship to engineers, lead knowledge-sharing initiatives, conduct design reviews, drive technical growth through thoughtful feedback, and contribute to building a culture of engineering excellence and continuous learning
• Balance innovation with pragmatic delivery – Drive features that move fast while establishing engineering standards; lead technical discussions on trade-offs; proactively identify and solve complex technical challenges; and own building applications that are both cutting-edge and production-ready
• Own production reliability and technical excellence – Lead troubleshooting of complex issues, drive system performance and scalability improvements, establish monitoring and observability practices, and own operational excellence of systems you architect

Benefits

• Base pay is one part of Fitch’s total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, long-term incentives, and other benefits sponsored by Fitch.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior